Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in patients with HER2+ early breast cancer (EBC).

Background: In HER2+ early breast cancer (EBC), we investigated tumor and immune changes during neoadjuvant treatment and their impact on residual disease (RD) biology and prognostic implications across 4 neoadjuvant studies of trastuzumab with or without lapatinib, and with or without chemotherapy: CALGB 40601, PAMELA, NeoALTTO and NSABP B-41.

Patients And Methods: We compared tumor and immune gene expression changes during neoadjuvant treatment and their association with with event-free survival (EFS) by uni- and multivariable Cox regression models in different cohorts and timepoints: 452 RD samples at baseline including 169 with a paired RD, and biomarker changes during neoadjuvant therapy, evaluating model performance via the c-index.

Results: Analysis of 169 paired tumor samples revealed a shift in intrinsic subtype proportions from HER2-Enriched at baseline (50.

Tumor-intrinsic kinome landscape of pancreatic cancer reveals new therapeutic approaches.

Effective therapies for pancreatic ductal adenocarcinoma (PDAC) have been largely elusive. Here, we perform Multiplexed kinase Inhibitor Bead Mass Spectrometry on 102 patient derived xenografts derived from 14 unique primary PDAC to define the tumor-intrinsic kinome landscape. Our findings uncover three kinome subgroups making up two tumor-intrinsic kinome subtypes that we call kinotypes.

Kinome state is predictive of cell viability in pancreatic cancer tumor and cancer-associated fibroblast cell lines.

Numerous aspects of cellular signaling are regulated by the kinome-the network of over 500 protein kinases that guides and modulates information transfer throughout the cell. The key role played by both individual kinases and assemblies of kinases organized into functional subnetworks leads to kinome dysregulation driving many diseases, particularly cancer. In the case of pancreatic ductal adenocarcinoma (PDAC), a variety of kinases and associated signaling pathways have been identified for their key role in the establishment of disease as well as its progression.

Purity Independent Subtyping of Tumors (PurIST) Pancreatic Cancer Classifier: Analytic Validation of a 16-RNA Expression Signature Distinguishing Basal and Classical Subtypes.

The two major molecular subtypes of pancreatic adenocarcinoma reportedly have differential response to FOLFIRINOX-based therapy. To promote rapid assignment of basal versus classical subtypes, an array-based single-sample classifier assay was developed and applied to 74 formalin-fixed, paraffin-embedded biopsy or resection specimens of known subtype based on transcriptomics. The Purity Independent Subtyping of Tumors (PurIST) algorithm assigns subtype based on relative expression of 16 RNAs counted by RNA sequencing (RNAseq) versus more practical array-based NanoString nCounter Elements XT technology.

Effect of hydrothermal pretreatment on leachate fed Scenedesmus sp. biomass solubilization and biogas production.

The aim of the present study was to assess the effect of hydrothermal pretreatment on the solubilization and anaerobic digestion (AD) of Scenedesmus sp. biomass. At first, the microalgae was cultivated in 5% fresh leachate (FL) to recover nutrients such as nitrogen and phosphorus.

Tumor-intrinsic and Cancer-associated Fibroblast Subtypes Independently Predict Outcomes in Pancreatic Cancer.

Objective: To assess the utility of tumor-intrinsic and cancer-associated fibroblast (CAF) subtypes of pancreatic ductal adenocarcinoma (PDAC) in predicting response to neoadjuvant therapy (NAT) and overall survival (OS).

Background: PDAC remains a deadly disease with limited treatment options, and both the tumor as well as the microenvironment play an important role in pathogenesis. Gene expression-based tumor-intrinsic subtypes (classical and basal-like) have been shown to predict outcomes, but tumor microenvironment subtypes are still evolving.

glmmPen: High Dimensional Penalized Generalized Linear Mixed Models.

Generalized linear mixed models (GLMMs) are widely used in research for their ability to model correlated outcomes with non-Gaussian conditional distributions. The proper selection of fixed and random effects is a critical part of the modeling process, where model misspecification may lead to significant bias. However, the joint selection of fixed and random effects has historically been limited to lower dimensional GLMMs, largely due to the use of criterion-based model selection strategies.

Evaluation of cell disruption methods for protein and coenzyme Q10 quantification in purple non-sulfur bacteria.

A recent focus has been on the recovery of single-cell protein and other nutritionally valuable bioproducts, such as Coenzyme Q10 (CoQ10) from purple non-sulfur bacteria (PNSB) biomass following wastewater treatment. However, due to PNSB's peculiar cell envelope (e.g.

Tumor Intrinsic Subtypes and Gene Expression Signatures in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Pooled Analysis of CALGB 40601, NeoALTTO, and NSABP B-41 Trials.

Importance: Biologic features may affect pathologic complete response (pCR) and event-free survival (EFS) after neoadjuvant chemotherapy plus ERBB2/HER2 blockade in ERBB2/HER2-positive early breast cancer (EBC).

Objective: To define the quantitative association between pCR and EFS by intrinsic subtype and by other gene expression signatures in a pooled analysis of 3 phase 3 trials: CALGB 40601, NeoALTTO, and NSABP B-41.

Design, Setting, And Participants: In this retrospective pooled analysis, 1289 patients with EBC received chemotherapy plus either trastuzumab, lapatinib, or the combination, with a combined median follow-up of 5.

Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects.

Modern biomedical datasets are increasingly high-dimensional and exhibit complex correlation structures. Generalized linear mixed models (GLMMs) have long been employed to account for such dependencies. However, proper specification of the fixed and random effects in GLMMs is increasingly difficult in high dimensions, and computational complexity grows with increasing dimension of the random effects.

Association of PIK3CA Mutation With Pathologic Complete Response and Outcome by Hormone Receptor Status and Intrinsic Subtype in Early-Stage ERBB2/HER2-Positive Breast Cancer.

Importance: PIK3CA mutations may be associated with outcomes of patients with ERBB2/HER2-positive early breast cancer (EBC).

Objectives: To assess if PIK3CA mutations among patients with ERBB2/HER2-positive EBC are associated with treatment response and outcome, and if these associations vary by hormone receptor (HR) status or intrinsic molecular subtype (IMS).

Design, Setting, And Participants: This cohort study derived data on 184 patients from the phase 3 neoadjuvant Cancer and Leukemia Group B (CALGB) 40601 trial that enrolled patients with ERBB2/HER2-positive EBC in North America between January 1, 2008, and December 31, 2012.

Sub-Cluster Identification through Semi-Supervised Optimization of Rare-Cell Silhouettes (SCISSORS) in single-cell RNA-sequencing.

Motivation: Single-cell RNA-sequencing (scRNA-seq) has enabled the molecular profiling of thousands to millions of cells simultaneously in biologically heterogenous samples. Currently, the common practice in scRNA-seq is to determine cell type labels through unsupervised clustering and the examination of cluster-specific genes. However, even small differences in analysis and parameter choosing can greatly alter clustering results and thus impose great influence on which cell types are identified.

Differential transcript usage analysis incorporating quantification uncertainty via compositional measurement error regression modeling.

Differential transcript usage (DTU) occurs when the relative expression of multiple transcripts arising from the same gene changes between different conditions. Existing approaches to detect DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. Here we propose a new method, CompDTU, that uses compositional regression to model the relative abundance proportions of each transcript that are of interest in DTU analyses.

Open-source curation of a pancreatic ductal adenocarcinoma gene expression analysis platform (pdacR) supports a two-subtype model.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease for which potent therapies have limited efficacy. Several studies have described the transcriptomic landscape of PDAC tumors to provide insight into potentially actionable gene expression signatures to improve patient outcomes. Despite centralization efforts from multiple organizations and increased transparency requirements from funding agencies and publishers, analysis of public PDAC data remains difficult.

Prognostic and Predictive Value of Immune-Related Gene Expression Signatures vs Tumor-Infiltrating Lymphocytes in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Correlative Analysis of the CALGB 40601 and PAMELA Trials.

Importance: Both tumor-infiltrating lymphocytes (TILs) assessment and immune-related gene expression signatures by RNA profiling predict higher pathologic complete response (pCR) and improved event-free survival (EFS) in patients with early-stage ERBB2/HER2-positive breast cancer. However, whether these 2 measures of immune activation provide similar or additive prognostic value is not known.

Objective: To examine the prognostic ability of TILs and immune-related gene expression signatures, alone and in combination, to predict pCR and EFS in patients with early-stage ERBB2/HER2-positive breast cancer treated in 2 clinical trials.

Kinetics of Biodiesel Production from Microalgae Using Microbubble Interfacial Technology.

As an alternative to fossil fuels, biodiesel can be a source of clean and environmentally friendly energy source. However, its commercial application is limited by expensive feedstock and the slow nature of the pretreatment step-acid catalysis. The conventional approach to carry out this reaction uses stirred tank reactors.

Balance between immunoregulatory B cells and plasma cells drives pancreatic tumor immunity.

Plasma cell responses are associated with anti-tumor immunity and favorable response to immunotherapy. B cells can amplify anti-tumor immune responses through antibody production; yet B cells in patients and tumor-bearing mice often fail to support this effector function. We identify dysregulated transcriptional program in B cells that disrupts differentiation of naive B cells into anti-tumor plasma cells.

Functional and biological heterogeneity of KRAS mutations.

Missense mutations at the three hotspots in the guanosine triphosphatase (GTPase) RAS-Gly, Gly, and Gln (commonly known as G12, G13, and Q61, respectively)-occur differentially among the three RAS isoforms. Q61 mutations in are infrequent and differ markedly in occurrence. Q61H is the predominant mutant (at 57%), followed by Q61R/L/K (collectively 40%), and Q61P and Q61E are the rarest (2 and 1%, respectively).