Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer

Background

With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify potential blood-based markers for six common human cancer types.

Methodology/Principal Findings

In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate) cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma) cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function.

Conclusion/Significance

The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the ‘omics’ era.     

Discovery and Validation of New Potential Biomarkers for Early Detection of Colon Cancer

Background

Accurate detection of characteristic proteins secreted by colon cancer tumor cells in biological fluids could serve as a biomarker for the disease. The aim of the present study was to identify and validate new serum biomarkers and demonstrate their potential usefulness for early diagnosis of colon cancer.

Methods

The study was organized in three sequential phases: 1) biomarker discovery, 2) technical and biological validation, and 3) proof of concept to test the potential clinical use of selected biomarkers. A prioritized subset of the differentially-expressed genes between tissue types (50 colon mucosa from cancer-free individuals and 100 normal-tumor pairs from colon cancer patients) was validated and further tested in a series of serum samples from 80 colon cancer cases, 23 patients with adenoma and 77 cancer-free controls.

Results

In the discovery phase, 505 unique candidate biomarkers were identified, with highly significant results and high capacity to discriminate between the different tissue types. After a subsequent prioritization, all tested genes (N = 23) were successfully validated in tissue, and one of them, COL10A1, showed relevant differences in serum protein levels between controls, patients with adenoma (p = 0.0083) and colon cancer cases (p = 3.2e-6).

Conclusion

We present a sequential process for the identification and further validation of biomarkers for early detection of colon cancer that identifies COL10A1 protein levels in serum as a potential diagnostic candidate to detect both adenoma lesions and tumor.

Impact

The use of a cheap serum test for colon cancer screening should improve its participation rates and contribute to decrease the burden of this disease.     

Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

Background

Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery.

Materials and Methods

Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode. Accurate Mass and Time (AMT) tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry.

Results

Proteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes.

Conclusions

Identification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for prostate cancer.     

Serum Protein Profile at Remission Can Accurately Assess Therapeutic Outcomes and Survival for Serous Ovarian Cancer

Background

Biomarkers play critical roles in early detection, diagnosis and monitoring of therapeutic outcome and recurrence of cancer. Previous biomarker research on ovarian cancer (OC) has mostly focused on the discovery and validation of diagnostic biomarkers. The primary purpose of this study is to identify serum biomarkers for prognosis and therapeutic outcomes of ovarian cancer.

Experimental Design

Forty serum proteins were analyzed in 70 serum samples from healthy controls (HC) and 101 serum samples from serous OC patients at three different disease phases: post diagnosis (PD), remission (RM) and recurrence (RC). The utility of serum proteins as OC biomarkers was evaluated using a variety of statistical methods including survival analysis.

Results

Ten serum proteins (PDGF-AB/BB, PDGF-AA, CRP, sFas, CA125, SAA, sTNFRII, sIL-6R, IGFBP6 and MDC) have individually good area-under-the-curve (AUC) values (AUC = 0.69–0.86) and more than 10 three-marker combinations have excellent AUC values (0.91–0.93) in distinguishing active cancer samples (PD & RC) from HC. The mean serum protein levels for RM samples are usually intermediate between HC and OC patients with active cancer (PD & RC). Most importantly, five proteins (sICAM1, RANTES, sgp130, sTNFR-II and sVCAM1) measured at remission can classify, individually and in combination, serous OC patients into two subsets with significantly different overall survival (best HR = 17, p<10⁻³).

Conclusion

We identified five serum proteins which, when measured at remission, can accurately predict the overall survival of serous OC patients, suggesting that they may be useful for monitoring the therapeutic outcomes for ovarian cancer.     

MALDI Profiling of Human Lung Cancer Subtypes

Background

Proteomics is expected to play a key role in cancer biomarker discovery. Although it has become feasible to rapidly analyze proteins from crude cell extracts using mass spectrometry, complex sample composition hampers this type of measurement. Therefore, for effective proteome analysis, it becomes critical to enrich samples for the analytes of interest. Despite that one-third of the proteins in eukaryotic cells are thought to be phosphorylated at some point in their life cycle, only a low percentage of intracellular proteins is phosphorylated at a given time.

Methodology/Principal Findings

In this work, we have applied chromatographic phosphopeptide enrichment techniques to reduce the complexity of human clinical samples. A novel method for high-throughput peptide profiling of human tumor samples, using Parallel IMAC and MALDI-TOF MS, is described. We have applied this methodology to analyze human normal and cancer lung samples in the search for new biomarkers. Using a highly reproducible spectral processing algorithm to produce peptide mass profiles with minimal variability across the samples, lineal discriminant-based and decision tree–based classification models were generated. These models can distinguish normal from tumor samples, as well as differentiate the various non–small cell lung cancer histological subtypes.

Conclusions/Significance

A novel, optimized sample preparation method and a careful data acquisition strategy is described for high-throughput peptide profiling of small amounts of human normal lung and lung cancer samples. We show that the appropriate combination of peptide expression values is able to discriminate normal lung from non-small cell lung cancer samples and among different histological subtypes. Our study does emphasize the great potential of proteomics in the molecular characterization of cancer.     

Serum S100A6 Concentration Predicts Peritoneal Tumor Burden in Mice with Epithelial Ovarian Cancer and Is Associated with Advanced Stage in Patients

Background

Ovarian cancer is the 5th leading cause of cancer related deaths in women. Five-year survival rates for early stage disease are greater than 94%, however most women are diagnosed in advanced stage with 5 year survival less than 28%. Improved means for early detection and reliable patient monitoring are needed to increase survival.

Methodology and Principal Findings

Applying mass spectrometry-based proteomics, we sought to elucidate an unanswered biomarker research question regarding ability to determine tumor burden detectable by an ovarian cancer biomarker protein emanating directly from the tumor cells. Since aggressive serous epithelial ovarian cancers account for most mortality, a xenograft model using human SKOV-3 serous ovarian cancer cells was established to model progression to disseminated carcinomatosis. Using a method for low molecular weight protein enrichment, followed by liquid chromatography and mass spectrometry analysis, a human-specific peptide sequence of S100A6 was identified in sera from mice with advanced-stage experimental ovarian carcinoma. S100A6 expression was documented in cancer xenografts as well as from ovarian cancer patient tissues. Longitudinal study revealed that serum S100A6 concentration is directly related to tumor burden predictions from an inverse regression calibration analysis of data obtained from a detergent-supplemented antigen capture immunoassay and whole-animal bioluminescent optical imaging. The result from the animal model was confirmed in human clinical material as S100A6 was found to be significantly elevated in the sera from women with advanced stage ovarian cancer compared to those with early stage disease.

Conclusions

S100A6 is expressed in ovarian and other cancer tissues, but has not been documented previously in ovarian cancer disease sera. S100A6 is found in serum in concentrations that correlate with experimental tumor burden and with clinical disease stage. The data signify that S100A6 may prove useful in detecting and/or monitoring ovarian cancer, when used in concert with other biomarkers.     

SPARC Is a Key Regulator of Proliferation, Apoptosis and Invasion in Human Ovarian Cancer

Background

Secreted protein acidic and rich in cysteine (SPARC), a calcium-binding matricellular glycoprotein, is implicated in the progression of many cancers. In this study, we investigated the expression and function of SPARC in ovarian cancer.

Methods

cDNA microarray analysis was performed to compare gene expression profiles of the highly invasive and the low invasive subclones derived from the SKOV3 human ovarian cancer cell line. Immunohistochemistry (IHC) staining was performed to investigate SPARC expression in a total of 140 ovarian tissue specimens. In functional assays, effects of SPARC knockdown on the biological behavior of ovarian cancer cells were investigated. The mechanisms of SPARC in ovarian cancer proliferation, apoptosis and invasion were also researched.

Results

SPARC was overexpressed in the highly invasive subclone compared with the low invasive subclone. High SPARC expression was associated with high stage, low differentiation, lymph node metastasis and poor prognosis of ovarian cancer. Knockdown of SPARC expression significantly suppressed ovarian cancer cell proliferation, induced cell apoptosis and inhibited cell invasion and metastasis.

Conclusion

SPARC is overexpressed in highly invasive subclone and ovarian cancer tissues and plays an important role in ovarian cancer growth, apoptosis and metastasis.     

BMI1, Stem Cell Factor Acting as Novel Serum-biomarker for Caucasian and African-American Prostate Cancer

Background

Lack of reliable predictive biomarkers is a stumbling block in the management of prostate cancer (CaP). Prostate-specific antigen (PSA) widely used in clinics has several caveats as a CaP biomarker. African-American CaP patients have poor prognosis than Caucasians, and notably the serum-PSA does not perform well in this group. Further, some men with low serum-PSA remain unnoticed for CaP until they develop disease. Thus, there is a need to identify a reliable diagnostic and predictive biomarker of CaP. Here, we show that BMI1 stem-cell protein is secretory and could be explored for biomarker use in CaP patients.

Methodology/Principal Findings

Semi-quantitative analysis of BMI1 was performed in prostatic tissues of TRAMP (autochthonous transgenic mouse model), human CaP patients, and in cell-based models representing normal and different CaP phenotypes in African-American and Caucasian men, by employing immunohistochemistry, immunoblotting and Slot-blotting. Quantitative analysis of BMI1 and PSA were performed in blood and culture-media of siRNA-transfected and non-transfected cells by employing ELISA. BMI1 protein is (i) secreted by CaP cells, (ii) increased in the apical region of epithelial cells and stromal region in prostatic tumors, and (iii) detected in human blood. BMI1 is detectable in blood of CaP patients in an order of increasing tumor stage, exhibit a positive correlation with serum-PSA and importantly is detectable in patients which exhibit low serum-PSA. The clinical significance of BMI1 as a biomarker could be ascertained from observation that CaP cells secrete this protein in higher levels than cells representative of benign prostatic hyperplasia (BPH).

Conclusions/Significance

BMI1 could be developed as a dual bio-marker (serum and biopsy) for the diagnosis and prognosis of CaP in Caucasian and African-American men. Though compelling these data warrant further investigation in a cohort of African-American patients.     

Integrative Proteomic Analysis of Serum and Peritoneal Fluids Helps Identify Proteins that Are Up-Regulated in Serum of Women with Ovarian Cancer

Background

We used intensive modern proteomics approaches to identify predictive proteins in ovary cancer. We identify up-regulated proteins in both serum and peritoneal fluid. To evaluate the overall performance of the approach we track the behavior of 20 validated markers across these experiments.

Methodology

Mass spectrometry based quantitative proteomics following extensive protein fractionation was used to compare serum of women with serous ovarian cancer to healthy women and women with benign ovarian tumors. Quantitation was achieved by isotopically labeling cysteine amino acids. Label-free mass spectrometry was used to compare peritoneal fluid taken from women with serous ovarian cancer and those with benign tumors. All data were integrated and annotated based on whether the proteins have been previously validated using antibody-based assays.

Findings

We selected 54 quantified serum proteins and 358 peritoneal fluid proteins whose case-control differences exceeded a predefined threshold. Seventeen proteins were quantified in both materials and 14 are extracellular. Of 19 validated markers that were identified all were found in cancer peritoneal fluid and a subset of 7 were quantified in serum, with one of these proteins, IGFBP1, newly validated here.

Conclusion

Proteome profiling applied to symptomatic ovarian cancer cases identifies a large number of up-regulated serum proteins, many of which are or have been confirmed by immunoassays. The number of currently known validated markers is highest in peritoneal fluid, but they make up a higher percentage of the proteins observed in both serum and peritoneal fluid, suggesting that the 10 additional markers in this group may be high quality candidates.     

Down-Regulation of miR-92 in Human Plasma Is a Novel Marker for Acute Leukemia Patients

Background

MicroRNAs are a family of 19- to 25-nucleotides noncoding small RNAs that primarily function as gene regulators. Aberrant microRNA expression has been described for several human malignancies, and this new class of small regulatory RNAs has both oncogenic and tumor suppressor functions. Despite this knowledge, there is little information regarding microRNAs in plasma especially because microRNAs in plasma, if exist, were thought to be digested by RNase. Recent studies, however, have revealed that microRNAs exist and escape digestion in plasma.

Methodology/Principal Findings

We performed microRNA microaray to obtain insight into microRNA deregulation in the plasma of a leukemia patient. We have revealed that microRNA-638 (miR-638) is stably present in human plasmas, and microRNA-92a (miR-92a) dramatically decreased in the plasmas of acute leukemia patients. Especially, the ratio of miR-92a/miR-638 in plasma was very useful for distinguishing leukemia patients from healthy body.

Conclusions/Significance

The ratio of miR-92a/miR-638 in plasma has strong potential for clinical application as a novel biomarker for detection of leukemia.     

Measurement of Phospholipids May Improve Diagnostic Accuracy in Ovarian Cancer

Background

More than two-thirds of women who undergo surgery for suspected ovarian neoplasm do not have cancer. Our previous results suggest phospholipids as potential biomarkers of ovarian cancer. In this study, we measured the serum levels of multiple phospholipids among women undergoing surgery for suspected ovarian cancer to identify biomarkers that better predict whether an ovarian mass is malignant.

Methodology/Principal Findings

We obtained serum samples preoperatively from women with suspected ovarian cancer enrolled through a prospective, population-based rapid ascertainment system. Samples were analyzed from all women in whom a diagnosis of epithelial ovarian cancer (EOC) was confirmed and from benign disease cases randomly selected from the remaining (non-EOC) samples. We measured biologically relevant phospholipids using liquid chromatography/electrospray ionization mass spectrometry. We applied a powerful statistical and machine learning approach, Hybrid huberized support vector machine (HH-SVM) to prioritize phospholipids to enter the biomarker models, and used cross-validation to obtain conservative estimates of classification error rates.

Results

The HH-SVM model using the measurements of specific combinations of phospholipids supplements clinical CA125 measurement and improves diagnostic accuracy. Specifically, the measurement of phospholipids improved sensitivity (identification of cases with preoperative CA125 levels below 35) among two types of cases in which CA125 performance is historically poor - early stage cases and those of mucinous histology. Measurement of phospholipids improved the identification of early stage cases from 65% (based on CA125) to 82%, and mucinous cases from 44% to 88%.

Conclusions/Significance

Levels of specific serum phospholipids differ between women with ovarian cancer and those with benign conditions. If validated by independent studies in the future, these biomarkers may serve as an adjunct at the time of clinical presentation, to distinguish between women with ovarian cancer and those with benign conditions with shared symptoms and features.     

NK Cell Phenotypic Modulation in Lung Cancer Environment

Background

Nature killer (NK) cells play an important role in anti-tumor immunotherapy. But it indicated that tumor cells impacted possibly on NK cell normal functions through some molecules mechanisms in tumor microenvironment.

Materials and methods

Our study analyzed the change about NK cells surface markers (NK cells receptors) through immunofluorescence, flow cytometry and real-time PCR, the killed function from mouse spleen NK cell and human high/low lung cancer cell line by co-culture. Furthermore we certificated the above result on the lung cancer model of SCID mouse.

Results

We showed that the infiltration of NK cells in tumor periphery was related with lung cancer patients'' prognosis. And the number of NK cell infiltrating in lung cancer tissue is closely related to the pathological types, size of the primary cancer, smoking history and prognosis of the patients with lung cancer. The expression of NK cells inhibitor receptors increased remarkably in tumor micro-environment, in opposite, the expression of NK cells activated receptors decrease magnificently.

Conclusions

The survival time of lung cancer patient was positively related to NK cell infiltration degree in lung cancer. Thus, the down-regulation of NKG2D, Ly49I and the up-regulation of NKG2A may indicate immune tolerance mechanism and facilitate metastasis in tumor environment. Our research will offer more theory for clinical strategy about tumor immunotherapy.     

The ADMR Receptor Mediates the Effects of Adrenomedullin on Pancreatic Cancer Cells and on Cells of the Tumor Microenvironment

Background

Adrenomedullin (AM) is highly expressed in pancreatic cancer and stimulates pancreatic cancer cells leading to increased tumor growth and metastasis. The current study examines the role of specific AM receptors on tumor and cells resembling the tumor microenvironment (human pancreatic stellate - HPSC, human umbilical vein – HUVEC and mouse lung endothelial cells - MLEC).

Methods and Findings

AM receptors ADMR and CRLR were present in HPSC, HUVEC and MLECs while PDAC cells possessed only ADMR receptors as assessed by RT-PCR and western blotting. All cell lines expressed and secreted AM as indicated by ELISA. The growth of each of the cell lines was stimulated by exogenous AM and inhibited by the antagonist AMA. AM also stimulated in vitro angiogenesis assessed by polygon formation of endothelial cell lines. SiRNA-mediated silencing of ADMR, but not CRLR, reduced basal growth of all cells examined and reduced polygon formation of endothelial cells in vitro. Orthotopic tumors developed with shADMR bearing cancer cells had dramatically reduced primary tumor volume (>90%) and lung and liver metastasis compared to shControl bearing cells. To validate ADMR as a potential therapeutic target, in vivo studies were conducted using neutral nanoliposomes to systemically deliver human siRNA to ADMR to silence human cancer cells and mouse siRNA to ADMR to silence mouse tumor stromal cells. Systemic silencing of both human and mouse ADMR had no obvious adverse effects but strongly reduced tumor development.

Conclusion

ADMR mediates the stimulatory effects of AM on cancer cells and on endothelial and stellate cells within the tumor microenvironment. These data support the further development of ADMR as a useful target treatment of pancreatic cancer.     

Steroids up-regulate p66Shc longevity protein in growth regulation by inhibiting its ubiquitination

Background

p66Shc, an isoform of Shc adaptor proteins, mediates diverse signals, including cellular stress and mouse longevity. p66Shc protein level is elevated in several carcinomas and steroid-treated human cancer cells. Several lines of evidence indicate that p66Shc plays a critical role in steroid-related carcinogenesis, and steroids play a role in its elevated levels in those cells without known mechanism.

Methods and Findings

In this study, we investigated the molecular mechanism by which steroid hormones up-regulate p66Shc protein level. In steroid-treated human prostate and ovarian cancer cells, p66Shc protein levels were elevated, correlating with increased cell proliferation. These steroid effects on p66Shc protein and cell growth were competed out by the respective antagonist. Further, actinomycin D and cyclohexamide could only partially block the elevated p66Shc protein level by steroids. Treatment with proteasomal inhibitors, but not lysosomal protease inhibitor, resulted in elevated p66Shc protein levels, even higher than that by steroids. Using prostate cancer cells as a model, immunoprecipitation revealed that androgens and proteasomal inhibitors reduce the ubiquitinated p66Shc proteins.

Conclusions

The data collectively indicate that functional steroid receptors are required in steroid up-regulation of p66Shc protein levels in prostate and ovarian cancer cells, correlating with cell proliferation. In these steroid-treated cells, elevated p66Shc protein level is apparently in part due to inhibiting its ubiquitination. The results may lead to an impact on advanced cancer therapy via the regulation of p66Shc protein by up-regulating its ubiquitination pathway.     

Polymorphic Variation of Genes in the Fibrinolytic System and the Risk of Ovarian Cancer

Introduction

The etiology of ovarian cancer is largely unknown. One hypothesis is that the inefficient removal of the blood clots and fibrin products which are deposited in the vicinity of the ovary by retrograde menstruation might be associated with an increased risk of ovarian cancer. Several single nucleotide polymorphisms within genes which comprise the fibrinolytic system have been shown to have functional effects on the rate of blood clot degradation. These were considered to be candidate genes in the present study.

Aim

We studied the genotype distributions of 12 functional SNPs of four genes (tPA, uPA PAI1 and TAFI) among 775 ovarian cancer cases and 889 controls.

Results

No significant associations were seen between any of the ten SNPs and the risk of ovarian cancer as a whole, or in any histologic subgroup.

Discussion

Germline known functional variants of genes in the fibrinolytic system are not associated with risk of ovarian cancer.     

Ataxia Telangiectasia Mutated and Rad3 Related (ATR) Protein Kinase Inhibition Is Synthetically Lethal in XRCC1 Deficient Ovarian Cancer Cells

Introduction

Ataxia telangiectasia mutated and Rad3 Related (ATR) protein kinase is a key sensor of single-stranded DNA associated with stalled replication forks and repair intermediates generated during DNA repair. XRCC1 is a critical enzyme in single strand break repair and base excision repair. XRCC1-LIG3 complex is also an important contributor to the ligation step of the nucleotide excision repair response.

Methods

In the current study, we investigated synthetic lethality in XRCC1 deficient and XRCC1 proficient Chinese Hamster ovary (CHO) and human ovarian cancer cells using ATR inhibitors (NU6027). In addition, we also investigated the ability of ATR inhibitors to potentiate cisplatin cytotoxicity in XRCC1 deficient and XRCC1 proficient CHO and human cancer cells. Clonogenic assays, alkaline COMET assays, γH2AX immunocytochemistry, FACS for cell cycle as well as FITC-annexin V flow cytometric analysis were performed.

Results

ATR inhibition is synthetically lethal in XRCC1 deficient cells as evidenced by increased cytotoxicity, accumulation of double strand DNA breaks, G2/M cell cycle arrest and increased apoptosis. Compared to cisplatin alone, combination of cisplatin and ATR inhibitor results in enhanced cytotoxicity in XRCC1 deficient cells compared to XRCC1 proficient cells.

Conclusions

Our data provides evidence that ATR inhibition is suitable for synthetic lethality application and cisplatin chemopotentiation in XRCC1 deficient ovarian cancer cells.     

ALDH1A1 Maintains Ovarian Cancer Stem Cell-Like Properties by Altered Regulation of Cell Cycle Checkpoint and DNA Repair Network Signaling

Objective

Aldehyde dehydrogenase (ALDH) expressing cells have been characterized as possessing stem cell-like properties. We evaluated ALDH+ ovarian cancer stem cell-like properties and their role in platinum resistance.

Methods

Isogenic ovarian cancer cell lines for platinum sensitivity (A2780) and platinum resistant (A2780/CP70) as well as ascites from ovarian cancer patients were analyzed for ALDH+ by flow cytometry to determine its association to platinum resistance, recurrence and survival. A stable shRNA knockdown model for ALDH1A1 was utilized to determine its effect on cancer stem cell-like properties, cell cycle checkpoints, and DNA repair mediators.

Results

ALDH status directly correlated to platinum resistance in primary ovarian cancer samples obtained from ascites. Patients with ALDH^HIGH displayed significantly lower progression free survival than the patients with ALDH^LOW cells (9 vs. 3 months, respectively p<0.01). ALDH1A1-knockdown significantly attenuated clonogenic potential, PARP-1 protein levels, and reversed inherent platinum resistance. ALDH1A1-knockdown resulted in dramatic decrease of KLF4 and p21 protein levels thereby leading to S and G2 phase accumulation of cells. Increases in S and G2 cells demonstrated increased expression of replication stress associated Fanconi Anemia DNA repair proteins (FANCD2, FANCJ) and replication checkpoint (pS317 Chk1) were affected. ALDH1A1-knockdown induced DNA damage, evidenced by robust induction of γ-H2AX and BAX mediated apoptosis, with significant increases in BRCA1 expression, suggesting ALDH1A1-dependent regulation of cell cycle checkpoints and DNA repair networks in ovarian cancer stem-like cells.

Conclusion

This data suggests that ovarian cancer cells expressing ALDH1A1 may maintain platinum resistance by altered regulation of cell cycle checkpoint and DNA repair network signaling.     

Multimodal Treatment Eliminates Cancer Stem Cells and Leads to Long-Term Survival in Primary Human Pancreatic Cancer Tissue Xenografts

Purpose

In spite of intense research efforts, pancreatic ductal adenocarcinoma remains one of the most deadly malignancies in the world. We and others have previously identified a subpopulation of pancreatic cancer stem cells within the tumor as a critical therapeutic target and additionally shown that the tumor stroma represents not only a restrictive barrier for successful drug delivery, but also serves as a paracrine niche for cancer stem cells. Therefore, we embarked on a large-scale investigation on the effects of combining chemotherapy, hedgehog pathway inhibition, and mTOR inhibition in a preclinical mouse model of pancreatic cancer.

Experimental Design

Prospective and randomized testing in a set of almost 200 subcutaneous and orthotopic implanted whole-tissue primary human tumor xenografts.

Results

The combined targeting of highly chemoresistant cancer stem cells as well as their more differentiated progenies, together with abrogation of the tumor microenvironment by targeting the stroma and enhancing tissue penetration of the chemotherapeutic agent translated into significantly prolonged survival in preclinical models of human pancreatic cancer. Most pronounced therapeutic effects were observed in gemcitabine-resistant patient-derived tumors. Intriguingly, the proposed triple therapy approach could be further enhanced by using a PEGylated formulation of gemcitabine, which significantly increased its bioavailability and tissue penetration, resulting in a further improved overall outcome.

Conclusions

This multimodal therapeutic strategy should be further explored in the clinical setting as its success may eventually improve the poor prognosis of patients with pancreatic ductal adenocarcinoma.