Sibgat Choudhury

The JAK2/STAT3 signaling pathway is required for growth of CD44+CD24– stem cell–like breast cancer cells in human tumors

Intratumor heterogeneity is a major clinical problem because tumor cell subtypes display variable sensitivity to therapeutics and may play different roles in progression. We previously characterized 2 cell populations in human breast tumors with distinct properties: CD44+CD24- cells that have stem cell-like characteristics, and CD44-CD24+ cells that resemble more differentiated breast cancer cells. Here we identified 15 genes required for cell growth or proliferation in CD44+CD24- human breast cancer cells in a large-scale loss-of-function screen and found that inhibition of several of these (IL6, PTGIS, HAS1, CXCL3, and PFKFB3) reduced Stat3 activation. We found that the IL-6/JAK2/Stat3 pathway was preferentially active in CD44+CD24- breast cancer cells compared with other tumor cell types, and inhibition of JAK2 decreased their number and blocked growth of xenografts. Our results highlight the differences between distinct breast cancer cell types and identify targets such as JAK2 and Stat3 that may lead to more specific and effective breast cancer therapies.

Epigenetic regulation of cell type-specific expression patterns in the human mammary epithelium

Differentiation is an epigenetic program that involves the gradual loss of pluripotency and acquisition of cell type–specific features. Understanding these processes requires genome-wide analysis of epigenetic and gene expression profiles, which have been challenging in primary tissue samples due to limited numbers of cells available. Here we describe the application of high-throughput sequencing technology for profiling histone and DNA methylation, as well as gene expression patterns of normal human mammary progenitor-enriched and luminal lineage-committed cells. We observed significant differences in histone H3 lysine 27 tri-methylation (H3K27me3) enrichment and DNA methylation of genes expressed in a cell type–specific manner, suggesting their regulation by epigenetic mechanisms and a dynamic interplay between the two processes that together define developmental potential. The technologies we developed and the epigenetically regulated genes we identified will accelerate the characterization of primary cell epigenomes and the dissection of human mammary epithelial lineage-commitment and luminal differentiation.

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

Background:Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation.Methods:Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a ‘high’ and a ‘low’ tumour microarray, respectively.Results:Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error.Conclusions:Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

Molecular profiling of human mammary gland links breast cancer risk to a p27(+) cell population with progenitor characteristics.

Early full-term pregnancy is one of the most effective natural protections against breast cancer. To investigate this effect, we have characterized the global gene expression and epigenetic profiles of multiple cell types from normal breast tissue of nulliparous and parous women and carriers of BRCA1 or BRCA2 mutations. We found significant differences in CD44(+) progenitor cells, where the levels of many stem cell-related genes and pathways, including the cell-cycle regulator p27, are lower in parous women without BRCA1/BRCA2 mutations. We also noted a significant reduction in the frequency of CD44(+)p27(+) cells in parous women and showed, using explant cultures, that parity-related signaling pathways play a role in regulating the number of p27(+) cells and their proliferation. Our results suggest that pathways controlling p27(+) mammary epithelial cells and the numbers of these cells relate to breast cancer risk and can be explored for cancer risk assessment and prevention.

Gene expression profiling of human breast tissue samples using SAGE-Seq

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Altered antisense-to-sense transcript ratios in breast cancer

Transcriptome profiling studies suggest that a large fraction of the genome is transcribed and many transcripts function independent of their protein coding potential. The relevance of noncoding RNAs (ncRNAs) in normal physiological processes and in tumorigenesis is increasingly recognized. Here, we describe consistent and significant differences in the distribution of sense and antisense transcripts between normal and neoplastic breast tissues. Many of the differentially expressed antisense transcripts likely represent long ncRNAs. A subset of genes that mainly generate antisense transcripts in normal but not cancer cells is involved in essential metabolic processes. These findings suggest fundamental differences in global RNA regulation between normal and cancer cells that might play a role in tumorigenesis.

Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality

BackgroundWe have witnessed significant progress in gene-based approaches to cancer prognostication, promising early intervention for high-risk patients and avoidance of overtreatment for low-risk patients. However, there has been less advancement in protein-based approaches, even though perturbed protein levels and post-translational modifications are more directly linked with phenotype. Most current, gene expression-based platforms require tissue lysis resulting in loss of structural and molecular information, and hence are blind to tumor heterogeneity and morphological features.ResultsHere we report an automated, integrated multiplex immunofluorescence in situ imaging approach that quantitatively measures protein biomarker levels and activity states in defined intact tissue regions where the biomarkers of interest exert their phenotype. Using this approach, we confirm that four previously reported prognostic markers, PTEN, SMAD4, CCND1 and SPP1, can predict lethal outcome of human prostate cancer. Furthermore, we show that two PI3K pathway-regulated protein activities, pS6 (RPS6-phosphoserines 235/236) and pPRAS40 (AKT1S1-phosphothreonine 246), correlate with prostate cancer lethal outcome as well (individual marker hazard ratios of 2.04 and 2.03, respectively). Finally, we incorporate these 2 markers into a novel 5-marker protein signature, SMAD4, CCND1, SPP1, pS6, and pPRAS40, which is highly predictive for prostate cancer-specific death. The ability to substitute PTEN with phospho-markers demonstrates the potential of quantitative protein activity state measurements on intact tissue.ConclusionsIn summary, our approach can reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens. We believe it is broadly applicable to not only cancer but other diseases, and propose that it should be well suited for prognostication at early stages of pathogenesis where key signaling protein levels and activities are perturbed.

Age- and Pregnancy-Associated DNA Methylation Changes in Mammary Epithelial Cells

Summary Postnatal mammary gland development and differentiation occur during puberty and pregnancy. To explore the role of DNA methylation in these processes, we determined the genome-wide DNA methylation and gene expression profiles of CD24+CD61+CD29hi, CD24+CD61+CD29lo, and CD24+CD61−CD29lo cell populations that were previously associated with distinct biological properties at different ages and reproductive stages. We found that pregnancy had the most significant effects on CD24+CD61+CD29hi and CD24+CD61+CD29lo cells, inducing distinct epigenetic states that were maintained through life. Integrated analysis of gene expression, DNA methylation, and histone modification profiles revealed cell-type- and reproductive-stage-specific changes. We identified p27 and TGFβ signaling as key regulators of CD24+CD61+CD29lo cell proliferation, based on their expression patterns and results from mammary gland explant cultures. Our results suggest that relatively minor changes in DNA methylation occur during luminal differentiation compared with the effects of pregnancy on CD24+CD61+CD29hi and CD24+CD61+CD29lo cells.

Differential expression of neurogenes among breast cancer subtypes identifies high risk patients

The nervous system is now recognized to be a relevant component of the tumor microenvironment. Receptors for neuropeptides and neurotransmitters have been identified in breast cancer. However, very little is known about the role of neurogenes in regulating breast cancer progression. Our purpose was to identify neurogenes associated with breast cancer tumorigenesis with a potential to be used as biomarker and/or targets for treatment. We used three databases of human genes: GeneGo, GeneCards and Eugenes to generate a list of 1266 relevant neurogenes. Then we used bioinformatics tools to interrogate two published breast cancer databases SAGE and MicMa (n=96) and generated a list of 7 neurogenes that are differentially express among breast cancer subtypes. The clinical potential was further investigated using the GOBO database (n=1881). We identified 6 neurogenes that are differentially expressed among breast cancer subtypes and whose expression correlates with prognosis. Histamine receptor1 (HRH1), neuropilin2 (NRP2), ephrin-B1 (EFNB1), neural growth factor receptor (NGFR) and amyloid precursor protein (APP) were differentially overexpressed in basal and HER2-enriched tumor samples and syntaxin 1A (STX1A) was overexpressed in HER2-enriched and luminal B tumors. Analysis of HRH1, NRP2, and STX1A expression using the GOBO database showed that their expression significantly correlated with a shorter overall survival (p < 0.0001) and distant metastasis-free survival (p < 0.0001). In contrast, elevated co-expression of NGFR, EFNB1 and APP was associated with longer overall (p < 0.0001) and metastasis-free survival (p < 0.0001). We propose that HRH1, NRP2, and STX1A can be used as prognostic biomarkers and therapeutic targets for basal and HER2-enriched breast cancer subtypes.