Dataset of breast thermography images for the detection of benign and malignant masses.

Thermographic image analysis is a subfield of diagnostic image processing aimed at detecting breast abnormalities in women at an early stage. It is a developing field of research and its effectiveness and scope require scientific assessment to be determined. An open-access dataset has been created for the scientific community to test and develop techniques for computational detection of normal and abnormal breast conditions from thermograms. This dataset is a valuable resource for researchers due to the scarcity of publicly available datasets of breast thermographic images. It includes thermographic images of the female chest area in three capture positions: anterior, left oblique and right oblique. The data set comes from 119 women ranging from 18 to 81 years of age. A table is attached to the dataset with the diagnosis of breast pathology, showing that 84 patients had benign pathology and 35 patients had malignant pathology. The diagnoses of women with healthy breast pathology are not included.

A candidate antibody drug for prevention of malaria.

Over 75% of malaria-attributable deaths occur in children under the age of 5 years. However, the first malaria vaccine recommended by the World Health Organization (WHO) for pediatric use, RTS,S/AS01 (Mosquirix), has modest efficacy. Complementary strategies, including monoclonal antibodies, will be important in efforts to eradicate malaria. Here we characterize the circulating B cell repertoires of 45 RTS,S/AS01 vaccinees and discover monoclonal antibodies for development as potential therapeutics. We generated >28,000 antibody sequences and tested 481 antibodies for binding activity and 125 antibodies for antimalaria activity in vivo. Through these analyses we identified correlations suggesting that sequences in Plasmodium falciparum circumsporozoite protein, the target antigen in RTS,S/AS01, may induce immunodominant antibody responses that limit more protective, but subdominant, responses. Using binding studies, mouse malaria models, biomanufacturing assessments and protein stability assays, we selected AB-000224 and AB-007088 for advancement as a clinical lead and backup. We engineered the variable domains (Fv) of both antibodies to enable low-cost manufacturing at scale for distribution to pediatric populations, in alignment with WHO's preferred product guidelines. The engineered clone with the optimal manufacturing and drug property profile, MAM01, was advanced into clinical development.

Massively parallel single-cell B-cell receptor sequencing enables rapid discovery of diverse antigen-reactive antibodies.

Obtaining full-length antibody heavy- and light-chain variable regions from individual B cells at scale remains a challenging problem. Here we use high-throughput single-cell B-cell receptor sequencing (scBCR-seq) to obtain accurately paired full-length variable regions in a massively parallel fashion. We sequenced more than 250,000 B cells from rat, mouse and human repertoires to characterize their lineages and expansion. In addition, we immunized rats with chicken ovalbumin and profiled antigen-reactive B cells from lymph nodes of immunized animals. The scBCR-seq data recovered 81% (n = 56/69) of B-cell lineages identified from hybridomas generated from the same set of B cells subjected to scBCR-seq. Importantly, scBCR-seq identified an additional 710 candidate lineages not recovered as hybridomas. We synthesized, expressed and tested 93 clones from the identified lineages and found that 99% (n = 92/93) of the clones were antigen-reactive. Our results establish scBCR-seq as a powerful tool for antibody discovery.

An entirely automated method to score DSS-induced colitis in mice by digital image analysis of pathology slides.

The DSS (dextran sulfate sodium) model of colitis is a mouse model of inflammatory bowel disease. Microscopic symptoms include loss of crypt cells from the gut lining and infiltration of inflammatory cells into the colon. An experienced pathologist requires several hours per study to score histological changes in selected regions of the mouse gut. In order to increase the efficiency of scoring, Definiens Developer software was used to devise an entirely automated method to quantify histological changes in the whole H&E slide. When the algorithm was applied to slides from historical drug-discovery studies, automated scores classified 88% of drug candidates in the same way as pathologists' scores. In addition, another automated image analysis method was developed to quantify colon-infiltrating macrophages, neutrophils, B cells and T cells in immunohistochemical stains of serial sections of the H&E slides. The timing of neutrophil and macrophage infiltration had the highest correlation to pathological changes, whereas T and B cell infiltration occurred later. Thus, automated image analysis enables quantitative comparisons between tissue morphology changes and cell-infiltration dynamics.

A hierarchy of self-renewing tumor-initiating cell types in glioblastoma.

The neural stem cell marker CD133 is reported to identify cells within glioblastoma (GBM) that can initiate neurosphere growth and tumor formation; however, instances of CD133(-) cells exhibiting similar properties have also been reported. Here, we show that some PTEN-deficient GBM tumors produce a series of CD133(+) and CD133(-) self-renewing tumor-initiating cell types and provide evidence that these cell types constitute a lineage hierarchy. Our results show that the capacities for self-renewal and tumor initiation in GBM need not be restricted to a uniform population of stemlike cells, but can be shared by a lineage of self-renewing cell types expressing a range of markers of forebrain lineage.

Microarray analysis of RNA extracted from formalin-fixed, paraffin-embedded and matched fresh-frozen ovarian adenocarcinomas.

BACKGROUND: Gene expression profiling of formalin-fixed, paraffin-embedded (FFPE) samples represents a valuable approach for advancing oncology diagnostics and enhancing retrospective clinical studies; however, at present, this methodology still requires optimization and thus has not been extensively used. Here, we utilized thorough quality control methods to assess RNA extracted from FFPE samples and then compared it to RNA extracted from matched fresh-frozen (FF) counterparts. We preformed genome-wide expression profiling of FF and FFPE ovarian serous adenocarcinoma sample pairs and compared their gene signatures to normal ovary samples. METHODS: RNA from FFPE samples was extracted using two different methods, Ambion and Agencourt, and its quality was determined by profiling starting total RNA on Bioanalyzer and by amplifying increasing size fragments of beta actin (ACTB) and claudin 3 (CLDN3) by reverse-transcriptase polymerase chain reaction. Five matched FF and FFPE ovarian serous adenocarcinoma samples, as well as a set of normal ovary samples, were profiled using whole genome Agilent microarrays. Reproducibility of the FF and FFPE replicates was measured using Pearson correlation, whereas comparison between the FF and FFPE samples was done using a Z-score analysis. RESULTS: Data analysis showed high reproducibility of expression within each FF and FFPE method, whereas matched FF and FFPE pairs demonstrated lower similarity, emphasizing an inherent difference between the two sample types. Z-score analysis of matched FF and FFPE samples revealed good concordance of top 100 differentially expressed genes with the highest correlation of 0.84. Genes characteristic of ovarian serous adenocarcinoma, including a well known marker CLDN3, as well as potentially some novel markers, were identified by comparing gene expression profiles of ovarian adenocarcinoma to those of normal ovary. CONCLUSION: Conclusively, we showed that systematic assessment of FFPE samples at the RNA level is essential for obtaining good quality gene expression microarray data. We also demonstrated that profiling of not only FF but also of FFPE samples can be successfully used to identify differentially expressed genes characteristic of ovarian carcinoma.

In vivo antitumor activity of MEK and phosphatidylinositol 3-kinase inhibitors in basal-like breast cancer models.

PURPOSE: The pathways underlying basal-like breast cancer are poorly understood, and as yet, there is no approved targeted therapy for this disease. We investigated the role of mitogen-activated protein kinase kinase (MEK) and phosphatidylinositol 3-kinase (PI3K) inhibitors as targeted therapies for basal-like breast cancer. EXPERIMENTAL DESIGN: We used pharmacogenomic analysis of a large panel of breast cancer cell lines with detailed accompanying molecular information to identify molecular predictors of response to a potent and selective inhibitor of MEK and also to define molecular mechanisms underlying combined MEK and PI3K targeting in basal-like breast cancer. Hypotheses were confirmed by testing in multiple tumor xenograft models. RESULTS: We found that basal-like breast cancer models have an activated RAS-like transcriptional program and show greater sensitivity to a selective inhibitor of MEK compared with models representative of other breast cancer subtypes. We also showed that loss of PTEN is a negative predictor of response to MEK inhibition, that treatment with a selective MEK inhibitor caused up-regulation of PI3K pathway signaling, and that dual blockade of both PI3K and MEK/extracellular signal-regulated kinase signaling synergized to potently impair the growth of basal-like breast cancer models in vitro and in vivo. CONCLUSIONS: Our studies suggest that single-agent MEK inhibition is a promising therapeutic modality for basal-like breast cancers with intact PTEN, and also provide a basis for rational combination of MEK and PI3K inhibitors in basal-like cancers with both intact and deleted PTEN.

Oncogenic activating mutations are associated with local copy gain.

Although activating mutations and gains in copy number are key mechanisms for oncogene activation, the relationship between the two is not well understood. In this study, we focused on KRAS copy gains and mutations in non-small cell lung cancer. We found that KRAS copy gains occur more frequently in tumors with KRAS activating mutations and are associated with large increases in KRAS expression. These copy gains tend to be more focal in tumors with activating mutations than in those with wild-type KRAS. Fluorescence in situ hybridization analysis revealed that some tumors have homogeneous low-level gains of the KRAS locus, whereas others have high-level amplification of KRAS, often in only a fraction of tumor cells. Associations between activating mutation and copy gains were also observed for other oncogenes (EGFR in non-small cell lung cancer, BRAF and NRAS in melanoma). Activating mutations were associated with copy gains only at the mutated oncogene locus but not other oncogene loci. However, KRAS activating mutations in colorectal cancer were not associated with copy gains. Future work is warranted to clarify the relationship among the different mechanisms of oncogene activation.