Aberrant lipid metabolism: an emerging diagnostic and therapeutic target in ovarian cancer

Genetic association of lipids and lipid-lowering drug target genes with Endometrial carcinoma: a drug target Mendelian randomization study

Background

Aberrant lipid metabolism is intricately linked to the development of endometrial cancer, and statin lipid-lowering medications are regarded as promising adjunctive therapies for future management of this malignancy. This study employed Mendelian randomization (MR) to explore the causal association between lipid traits and endometrial cancer while assessing the potential impact of drug targets on lower lipids on endometrial cancer.

Method

Two-sample Mendelian randomization was employed to probe the causal association between lipid traits and endometrial carcinoma. Drug-target Mendelian randomization was also utilized to identify potential drug-target genes for managing endometrial carcinoma. In instances where lipid-mediated effects through particular drug targets were notable, the impacts of these drug targets on endometrial carcinoma risk factors were investigated to bolster the findings.

Result

No causal association between genetically predicted lipid traits (LDL-C, TG, TC, and HDL-C) and EC was found in two-sample Mendelian randomization. In drug target Mendelian randomization, genetic modeling of apolipoprotein B (APOB) (OR [95%CI]=0.31, [0.16-0.60]; p=4.73e-04) and cholesteryl ester transfer protein (CETP) (OR [95%CI]=1.83, [1.38-2.43]; p=2.91e-05) genetic mimicry was associated with non-endometrioid carcinoma.

Conclusion

The results of our MR study revealed no causal association between genetically predicted lipid traits (LDL-C, TG, TC, and HDL-C) and EC. Among the six lipid-lowering drug targets, we observed a significant association between lower predicted APOB levels and higher CETP levels with an increased risk of endometrioid carcinoma. These findings provide novel insights into the importance of lipid regulation in individuals with endometrial carcinoma, warranting further clinical validation and mechanistic investigations.

The Contribution of Lipidomics in Ovarian Cancer Management: A Systematic Review

Lipidomics is a comprehensive study of all lipid components in living cells, serum, plasma, or tissues, with the aim of discovering diagnostic, prognostic, and predictive biomarkers for diseases such as malignant tumors. This systematic review evaluates studies, applying lipidomics to the diagnosis, prognosis, prediction, and differentiation of malignant and benign ovarian tumors. A literature search was performed in PubMed, Science Direct, and SciFinder. Only publications written in English after 2012 were included. Relevant citations were identified from the reference lists of primary included studies and were also included in our list. All studies included referred to the application of lipidomics in serum/plasma samples from human cases of OC, some of which also included tumor tissue samples. In some of the included studies, metabolome analysis was also performed, in which other metabolites were identified in addition to lipids. Qualitative data were assessed, and the risk of bias was determined using the ROBINS-I tool. A total of twenty-nine studies were included, fifteen of which applied non-targeted lipidomics, seven applied targeted lipidomics, and seven were reviews relevant to our objectives. Most studies focused on the potential application of lipidomics in the diagnosis of OC and showed that phospholipids and sphingolipids change most significantly during disease development. In conclusion, this systematic review highlights the potential contribution of lipids as biomarkers in OC management.

Evaluating Alkaline Phosphatase-Instructed Self-Assembly of d-Peptides for Selectively Inhibiting Ovarian Cancer Cells

Cancer is a major public health concern requiring novel treatment approaches. Enzyme-instructed self-assembly (EISA) provides a unique approach for selectively inhibiting cancer cells. However, the structure and activity correlation of EISA remains to be explored. This study investigates new EISA substrates of alkaline phosphatase (ALP) to hinder ovarian cancer cells. Analogues 2-8 were synthesized by modifying the amino acid residues of a potent EISA substrate 1 that effectively inhibits the growth of OVSAHO, a high-grade serous ovarian cancer (HGSOC) cell line. The efficacy of 2-8 against OVSAHO was assessed, along with the combination of substrate 1 with clinically used drugs. The results reveal that substrate 1 displays the highest cytotoxicity against OVSAHO cells, with an IC50 of around 8 μM. However, there was limited synergism observed between substrate 1 and the tested clinically used drugs. These findings indicate that EISA likely operates through a distinct mechanism that necessitates further elucidation.

Posttranslational control of lipogenesis in the tumor microenvironment

Metabolic reprogramming of cancer cells within the tumor microenvironment typically occurs in response to increased nutritional, translation and proliferative demands. Altered lipid metabolism is a marker of tumor progression that is frequently observed in aggressive tumors with poor prognosis. Underlying these abnormal metabolic behaviors are posttranslational modifications (PTMs) of lipid metabolism-related enzymes and other factors that can impact their activity and/or subcellular localization. This review focuses on the roles of these PTMs and specifically on how they permit the re-wiring of cancer lipid metabolism, particularly within the context of the tumor microenvironment.

Lipid metabolism in tumor microenvironment: novel therapeutic targets

Bioactive lipid molecules have been proposed to play important roles linking obesity/metabolic syndrome and cancers. Studies reveal that aberrant lipid metabolic signaling can reprogram cancer cells and non-cancer cells in the tumor microenvironment, contributing to cancer initiation, progression, metastasis, recurrence, and poor therapeutic response. Existing evidence indicates that controlling lipid metabolism can be a potential strategy for cancer prevention and therapy. By reviewing the current literature on the lipid metabolism in various cancers, we summarized major lipid molecules including fatty acids and cholesterol as well as lipid droplets and discussed their critical roles in cancer cells and non-cancer in terms of either promoting- or anti-tumorigenesis. This review provides an overview of the lipid molecules in cellular entities and their tumor microenvironment, adding to the existing knowledge with lipid metabolic reprogramming in immune cells and cancer associated cells. Comprehensive understanding of the regulatory role of lipid metabolism in cellular entities and their tumor microenvironment will provide a new direction for further studies, in a shift away from conventional cancer research. Exploring the lipid-related signaling targets that drive or block cancer development may lead to development of novel anti-cancer strategies distinct from traditional approaches for cancer prevention and treatment.

Targeting lipid metabolism in the treatment of ovarian cancer

Cancer cells undergo alterations in lipid metabolism to support their high energy needs, tumorigenesis and evade an anti-tumor immune response. Alterations in fatty acid production are controlled by multiple enzymes, chiefly Acetyl CoA Carboxylase, ATP-Citrate Lyase, Fatty Acid Synthase, and Stearoyl CoA Desaturase 1. Ovarian cancer (OC) is a common gynecological malignancy with a high rate of aggressive carcinoma progression and drug resistance. The accumulation of unsaturated fatty acids in ovarian cancer supports cell growth, increased cancer cell migration, and worse patient outcomes. Ovarian cancer cells also expand their lipid stores via increased uptake of lipids using fatty acid translocases, fatty acid-binding proteins, and low-density lipoprotein receptors. Furthermore, increased lipogenesis and lipid uptake promote chemotherapy resistance and dampen the adaptive immune response needed to eliminate tumors. In this review, we discuss the role of lipid synthesis and metabolism in driving tumorigenesis and drug resistance in ovarian cancer conferring poor prognosis and outcomes in patients. We also cover some aspects of how lipids fuel ovarian cancer stem cells, and how these metabolic alterations in intracellular lipid content could potentially serve as biomarkers of ovarian cancer.

Study on the levels of N-nitrosamine compounds and untargeted metabolomics in patients with colorectal cancer

Plasma samples were collected from 34 patients with advanced CRC and 92 healthy persons (control group), and the levels of 9 VNAs were measured using GC-MS. Untargeted metabolomics analysis was performed using LC-MS/MS. Partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis were used to determine differential metabolites between the 2 groups. Receiver operating characteristic (ROC) curve analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed on the differential metabolites. It turned out that the detection rates of N-nitrosodimethylamine (NDMA) and N-nitrosopyrrolidine (NPYR) in patients with CRC were higher than in the control group (P < 0.05). N-nitrosomethylethylamine (NMEA) and N-nitrosodiphenylamine (NDPhA) were not detected in CRC patients. NDMA, N-nitrosodibutylamine (NDBA), N-nitrosopiperidine (NPIP), and NPYR were detected in male and female patients with CRC. There was no difference in VNAs exposure between the sexes of CRC patients. In the positive and negative ion mode, a total of 132 differential metabolites and 6 differential metabolic pathways were detected. Adenosine 5'-monophosphate, hypoxanthine, 11,12-epoxy-(5Z,8Z,11Z)-icosatrienoic acid, 16(R)-HETE, acetylcarnitine, and lysophosphatidic acid (LPA 20:5, LPA 20:4) were candidate biomarkers with higher predictive value. Hypoxanthine and xanthine metabolic pathways were associated with changes in VNAs in CRC patients. In summary, the effects of changes of VNAs in the plasma of CRC patients (especially NDMA and NPYR) on the progression of CRC should attract attention. Abnormalities of adenine and guanine and downstream hypoxanthine-xanthine metabolic pathways were closely related to changes of VNAs and metabolomics in CRC patients.

Molecular response to PARP1 inhibition in ovarian cancer cells as determined by mass spectrometry based proteomics

BACKGROUND

Poly (ADP)-ribose polymerase (PARP) inhibitors have entered routine clinical practice for the treatment of high-grade serous ovarian cancer (HGSOC), yet the molecular mechanisms underlying treatment response to PARP1 inhibition (PARP1i) are not fully understood.

METHODS

Here, we used unbiased mass spectrometry based proteomics with data-driven protein network analysis to systematically characterize how HGSOC cells respond to PARP1i treatment.

RESULTS

We found that PARP1i leads to pronounced proteomic changes in a diverse set of cellular processes in HGSOC cancer cells, consistent with transcript changes in an independent perturbation dataset. We interpret decreases in the levels of the pro-proliferative transcription factors SP1 and β-catenin and in growth factor signaling as reflecting the anti-proliferative effect of PARP1i; and the strong activation of pro-survival processes NF-κB signaling and lipid metabolism as PARPi-induced adaptive resistance mechanisms. Based on these observations, we nominate several protein targets for therapeutic inhibition in combination with PARP1i. When tested experimentally, the combination of PARPi with an inhibitor of fatty acid synthase (TVB-2640) has a 3-fold synergistic effect and is therefore of particular pre-clinical interest.

CONCLUSION

Our study improves the current understanding of PARP1 function, highlights the potential that the anti-tumor efficacy of PARP1i may not only rely on DNA damage repair mechanisms and informs on the rational design of PARP1i combination therapies in ovarian cancer.

Quantitative global lipidomics analysis of patients with ovarian cancer versus benign adnexal mass

Altered lipid metabolism has emerged as an important feature of ovarian cancer (OC), yet the translational potential of lipid metabolites to aid in diagnosis and triage remains unproven. We conducted a multi-level interrogation of lipid metabolic phenotypes in patients with adnexal masses, integrating quantitative lipidomics profiling of plasma and ascites with publicly-available tumor transcriptome data. Using Sciex Lipidyzer, we assessed concentrations of > 500 plasma lipids in two patient cohorts-(i) a pilot set of 100 women with OC (50) or benign tumor (50), and (ii) an independent set of 118 women with malignant (60) or benign (58) adnexal mass. 249 lipid species and several lipid classes were significantly reduced in cases versus controls in both cohorts (FDR < 0.05). 23 metabolites-triacylglycerols, phosphatidylcholines, cholesterol esters-were validated at Bonferroni significance (P < 9.16 × 10-5). Certain lipids exhibited greater alterations in early- (diacylglycerols) or late-stage (lysophospholipids) cases, and multiple lipids in plasma and ascites were positively correlated. Lipoprotein receptor gene expression differed markedly in OC versus benign tumors. Importantly, several plasma lipid species, such as DAG(16:1/18:1), improved the accuracy of CA125 in differentiating early-stage OC cases from benign controls, and conferred a 15-20% increase in specificity at 90% sensitivity in multivariate models adjusted for age and BMI. This study provides novel insight into systemic and local lipid metabolic differences between OC and benign disease, further implicating altered lipid uptake in OC biology, and advancing plasma lipid metabolites as a complementary class of circulating biomarkers for OC diagnosis and triage.

A Narrative Review of the Role of Diet and Lifestyle Factors in the Development and Prevention of Endometrial Cancer

Simple Summary

The incidence and prevalence of endometrial cancer is increasing globally. The main factors involved in this increase have been the way women live today and what they eat and drink. In fact, the obesity pandemic that is sweeping across the planet is considered to be the main contributory feature. This review aims to introduce to a new audience, those that are not experts in the field, what is known about the different types of endometrial cancer and the mechanisms for their induction and protection. We also seek to summarise the existing knowledge on dietary and lifestyle factors that prevent endometrial development in susceptible populations and identify the main problem in this arena; the paucity of research studies and clinical trials that investigate the interaction(s) between diet, lifestyle and endometrial cancer risk whilst highlighting those areas of promise that should be further investigated.

Abstract

Endometrial cancer is the most common cancer affecting the reproductive organs of women living in higher-income countries. Apart from hormonal influences and genetic predisposition, obesity and metabolic syndrome are increasingly recognised as major factors in endometrial cancer risk, due to changes in lifestyle and diet, whereby high glycaemic index and lipid deposition are prevalent. This is especially true in countries where micronutrients, such as vitamins and minerals are exchanged for high calorific diets and a sedentary lifestyle. In this review, we will survey the currently known lifestyle factors, dietary requirements and hormonal changes that increase an individual’s risk for endometrial cancer and discuss their relevance for clinical management. We also examine the evidence that everyday factors and clinical interventions have on reducing that risk, such that informed healthy choices can be made. In this narrative review, we thus summarise the dietary and lifestyle factors that promote and prevent the incidence of endometrial cancer.

A Novel Two-Lipid Signature Is a Strong and Independent Prognostic Factor in Ovarian Cancer

Simple Summary

Most ovarian cancer patients initially show a response to primary treatments, but the development of refractory disease is a major problem. Currently, there are no blood-based prognostic biomarkers, and the prognosis of a patient is determined by the International Federation of Gynecology and Obstetrics (FIGO) stage and residual disease after cytoreductive surgery. In this study, we developed and validated a novel test based on the ratio of two circulatory lipids that enables the prognostic stratification of ovarian cancer patients at the time of diagnosis, prior to any oncological treatments. The translational relevance of this test is to find those patients with poor prognosis early on, and to identify patients that are at high risk of recurrence despite complete cytoreduction. Thus, the test enables the early direction of novel targeted therapies to those ovarian cancer patients at greatest risk of recurrence and death.

Abstract

Epithelial ovarian cancer (EOC) generally responds well to oncological treatments, but the eventual development of a refractory disease is a major clinical problem. Presently, there are no prognostic blood-based biomarkers for the stratification of EOC patients at the time of diagnosis. We set out to assess and validate the prognostic utility of a novel two-lipid signature, as the lipidome is known to be markedly aberrant in EOC patients. The study consisted of 499 women with histologically confirmed EOC that were prospectively recruited at the university hospitals in Turku (Finland) and Charité (Berlin, Germany). Lipidomic screening by tandem liquid chromatography–mass spectrometry (LC-MS/MS) was performed for all baseline serum samples of these patients, and additionally for 20 patients of the Turku cohort at various timepoints. A two-lipid signature, based on the ratio of the ceramide Cer(d18:1/18:0) and phosphatidylcholine PC(O-38:4), showed consistent prognostic performance in all investigated study cohorts. In the Turku cohort, the unadjusted hazard ratios (HRs) per standard deviation (SD) (95% confidence interval) were 1.79 (1.40, 2.29) for overall and 1.40 (1.14, 1.71) for progression-free survival. In a Charité cohort incorporating only stage III completely resected patients, the corresponding HRs were 1.59 (1.08, 2.35) and 1.53 (1.02, 2.30). In linear-mixed models predicting progression of the disease, the two-lipid signature showed higher performance (beta per SD increase 1.99 (1.38, 2.97)) than cancer antigen 125 (CA-125, 1.78 (1.13, 2.87)). The two-lipid signature was able to identify EOC patients with an especially poor prognosis at the time of diagnosis, and also showed promise for the detection of disease relapse.

Serum lipid profiling analysis and potential marker discovery for ovarian cancer based on liquid chromatography-Mass spectrometry

Low early diagnosis rate and unclear pathogenesis are the primary reasons for the high mortality of epithelial ovarian cancer (EOC). Lipidomics is a powerful tool for marker discovery and mechanism explanation. Hence, a ultra high-performance liquid chromatography-mass spectrometry based non-targeted lipidomics analysis was performed to acquire lipid profiling of 153 serum samples including healthy control (HC, n = 50), benign ovarian tumor (BOT, n = 41), and EOC (n = 62) to reveal lipid disturbance, then differential lipids were verified in another sample set including 187 sera. Significant lipid disturbance occurred in BOT and EOC, fatty acid, lyso-phosphatidylcholine, and lyso-phosphatidylethanolamine were observed to be increased in BOT and EOC subjects, while phosphatidylcoline, ether phosphatidylcoline (PC-O), ether phosphatidylethanolamine (PE-O), and sphingomyelin significantly decreased. Compared with BOT, PC-Os and PE-Os presented a greater reduction in EOC, and serum ceramide increased only in EOC. Moreover, potential markers consisting of 4 lipids were defined and validated for EOC diagnosis. High areas under the curve (0.854∼0.865 and 0.903∼0.923 for distinguishing EOC and early EOC from non-cancer, respectively) as well as good specificity and sensitivity were obtained. This study not only revealed the characteristics of lipid metabolism in EOC, but also provided a potential marker pattern for aiding EOC diagnosis.

Circulating Lysophosphatidylcholines, Phosphatidylcholines, Ceramides, and Sphingomyelins and Ovarian Cancer Risk: A 23-Year Prospective Study

BACKGROUND

Experimental evidence supports a role of lipid dysregulation in ovarian cancer progression. We estimated associations with ovarian cancer risk for circulating levels of four lipid groups, previously hypothesized to be associated with ovarian cancer, measured 3-23 years before diagnosis.

METHODS

Analyses were conducted among cases (N = 252) and matched controls (N = 252) from the Nurses' Health Studies. We used logistic regression adjusting for risk factors to investigate associations of lysophosphatidylcholines (LPCs), phosphatidylcholines (PCs), ceramides (CERs), and sphingomyelins (SMs) with ovarian cancer risk overall and by histotype. A modified Bonferroni approach (0.05/4 = 0.0125, four lipid groups) and the permutation-based Westfall and Young approach were used to account for testing multiple correlated hypotheses. Odds ratios (ORs; 10th-90th percentile), and 95% confidence intervals of ovarian cancer risk were estimated. All statistical tests were two-sided.

RESULTS

SM sum was statistically significantly associated with ovarian cancer risk (OR = 1.97, 95% CI = 1.16 to 3.32; P = .01/permutation-adjusted P = .20). C16:0 SM, C18:0 SM, and C16:0 CERs were suggestively associated with risk (OR = 1.95-2.10; P = .004-.01; permutation-adjusted P = .08-.21). SM sum, C16:0 SM, and C16:0 CER had stronger odds ratios among postmenopausal women (OR = 2.16-3.22). Odds ratios were similar for serous/poorly differentiated and endometrioid/clear cell tumors, although C18:1 LPC and LPC to PC ratio were suggestively inversely associated, whereas C18:0 SM was suggestively positively associated with risk of endometrioid/clear cell tumors. No individual metabolites were associated with risk when using the permutation-based approach.

CONCLUSIONS

Elevated levels of circulating SMs 3-23 years before diagnosis were associated with increased risk of ovarian cancer, regardless of histotype, with stronger associations among postmenopausal women. Further studies are required to validate and understand the role of lipid dysregulation in ovarian carcinogenesis.

The application of metabolomics in ovarian cancer management: a systematic review

Metabolomics, the global analysis of metabolites in a biological specimen, could potentially provide a fast method of biomarker identification for ovarian cancer. This systematic review aims to examine findings from studies that apply metabolomics to the diagnosis, prognosis, treatment, and recurrence of ovarian cancer. A systematic search of English language publications was conducted on PubMed, Science Direct, and SciFinder. It was augmented by a snowball strategy, whereby further relevant studies are identified from reference lists of included studies. Studies in humans with ovarian cancer which focus on metabolomics of biofluids and tumor tissue were included. No restriction was placed on the time of publication. A separate review of targeted metabolomic studies was conducted for completion. Qualitative data were summarized in a comprehensive table. The studies were assessed for quality and risk of bias using the ROBINS-I tool. 32 global studies were included in the main systematic review. Most studies applied metabolomics to diagnosing ovarian cancer, within which the most frequently reported metabolite changes were a down-regulation of phospholipids and amino acids: histidine, citrulline, alanine, and methionine. Dysregulated phospholipid metabolism was also reported in the separately reviewed 18 targeted studies. Generally, combinations of more than one significant metabolite as a panel, in different studies, achieved a higher sensitivity and specificity for diagnosis than a single metabolite; for example, combinations of different phospholipids. Widespread metabolite differences were observed in studies examining prognosis, treatment, and recurrence, and limited conclusions could be drawn. Cellular processes of proliferation and invasion may be reflected in metabolic changes present in poor prognosis and recurrence. For example, lower levels of lysine, with increased cell invasion as an underlying mechanism, or glutamine dependency of rapidly proliferating cancer cells. In conclusion, this review highlights potential metabolites and biochemical pathways which may aid the clinical care of ovarian cancer if further validated.

Coordination of Nanoconjugation with an Antigen/Antibody for Efficient Detection of Gynecological Tumors

Cervical, ovarian, and endometrial cancers are common in the female reproductive system. Cervical cancer starts from the cervix, while ovarian cancer develops when abnormal cells grow in the ovary. Endometrial or uterine cancer starts from the lining of the womb in the endometrium. Approximately 12,000 women are affected every year by cervical cancer in the United States. Squamous cell carcinoma antigen (SCC-Ag) is a well-established biomarker in serum for diagnosing gynecological cancers, and its levels were observed to be elevated in cervical, ovarian, and endometrial cancer patients. Moreover, SCC-Ag was used to identify the tumor size and progression stages. Various biosensing systems have been proposed to identify SCC-Ag; herein, enhanced interdigitated electrode sensing is presented with the use of gold nanoparticles (GNPs) to conjugate an antigen/antibody. It was proved that the limit of detection is 62.5 fM in the case of antibody-GNP, which is 2-fold higher than that by SCC-Ag-GNP. Furthermore, the antibody-GNP-modified surface displays greater current increases with concomitant dose-dependent SCC-Ag levels. High analytical performance was shown by the discrimination against α-fetoprotein and CYFRA 21-1 at 1 pM. An enhanced sensing system is established for gynecological tumors, representing an advance from the earlier detection methods.

An integrative tissue-network approach to identify and test human disease genes

Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of human biology experiments. Here we developed diseaseQUEST, an integrative approach that combines data from human genome-wide disease studies with in silico network models of tissue- and cell-type-specific function in model organisms to prioritize candidates within functionally conserved processes and pathways. We used diseaseQUEST to predict candidate genes for 25 different diseases and traits, including cancer, longevity, and neurodegenerative diseases. Focusing on Parkinson's disease (PD), a diseaseQUEST-directed Caenhorhabditis elegans behavioral screen identified several candidate genes, which we experimentally verified and found to be associated with age-dependent motility defects mirroring PD clinical symptoms. Furthermore, knockdown of the top candidate gene, bcat-1, encoding a branched chain amino acid transferase, caused spasm-like 'curling' and neurodegeneration in C. elegans, paralleling decreased BCAT1 expression in PD patient brains. diseaseQUEST is modular and generalizable to other model organisms and human diseases of interest.

Ovarian tumours of different histologic type and clinical stage induce similar changes in lipid metabolism

Background

Previous results obtained from serum samples of late-stage, high-grade serous ovarian carcinoma patients showed large alterations in lipid metabolism. To validate and extend the results, we studied lipidomic changes in early-stage ovarian tumours. In addition to serous ovarian cancer, we investigated whether these changes occur in mucinous and endometrioid histological subtypes as well.

Methods

Altogether, 354 serum or plasma samples were collected from three centres, one from Germany and two from Finland. We performed lipidomic analysis of samples from patients with malignant (N = 138) or borderline (N = 25) ovarian tumours, and 191 controls with benign pathology. These results were compared to previously published data.

Results

We found 39 lipids that showed consistent alteration both in early- and late-stage ovarian cancer patients as well as in pre- and postmenopausal women. Most of these changes were already significant at an early stage and progressed with increasing stage. Furthermore, 23 lipids showed similar alterations in all investigated histological subtypes.

Conclusions

Changes in lipid metabolism due to ovarian cancer occur in early-stage disease but intensify with increasing stage. These changes occur also in other histological subtypes besides high-grade serous carcinoma. Understanding lipid metabolism in ovarian cancer may lead to new therapeutic and diagnostic alternatives.

The surgical intelligent knife distinguishes normal, borderline and malignant gynaecological tissues using rapid evaporative ionisation mass spectrometry (REIMS)

Background

Survival from ovarian cancer (OC) is improved with surgery, but surgery can be complex and tumour identification, especially for borderline ovarian tumours (BOT), is challenging. The Rapid Evaporative Ionisation Mass Spectrometric (REIMS) technique reports tissue histology in real-time by analysing aerosolised tissue during electrosurgical dissection.

Methods

Aerosol produced during diathermy of tissues was sampled with the REIMS interface. Histological diagnosis and mass spectra featuring complex lipid species populated a reference database on which principal component, linear discriminant and leave-one-patient-out cross-validation analyses were performed.

Results

A total of 198 patients provided 335 tissue samples, yielding 3384 spectra. Cross-validated OC classification vs separate normal tissues was high (97·4% sensitivity, 100% specificity). BOT were readily distinguishable from OC (sensitivity 90.5%, specificity 89.7%). Validation with fresh tissue lead to excellent OC detection (100% accuracy). Histological agreement between iKnife and histopathologist was very good (kappa 0.84, P < 0.001, z = 3.3). Five predominantly phosphatidic acid (PA(36:2)) and phosphatidyl-ethanolamine (PE(34:2)) lipid species were identified as being significantly more abundant in OC compared to normal tissue or BOT (P < 0.001, q < 0.001).

Conclusions

The REIMS iKnife distinguishes gynaecological tissues by analysing mass-spectrometry-derived lipidomes from tissue diathermy aerosols. Rapid intra-operative gynaecological tissue diagnosis may improve surgical care when histology is unknown, leading to personalised operations tailored to the individual.

Transcriptome sequencing identified hub genes for hepatocellular carcinoma by weighted-gene co-expression analysis

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide, and it remains a challenge to understand the genetic mechanisms underlying hepatocarcinogenesis. A global gene network of differential expression profiles in HCC has yet to be fully characterized. In the present study, we performed transcriptome sequencing (mRNA and lncRNA) in liver cancer and cirrhotic tissues of nine HCC patients. We identified differentially expressed genes (DEGs) and constructed a weighted gene co-expression network for the DEGs. In total, 755 DEGs (747 mRNA and eight lncRNA) were identified, and several co-expression modules were significantly associated with HCC clinical traits, including tumor location, tumor grade, and the α-fetoprotein (AFP) level. Of note, we identified 15 hub genes in the module associated with AFP level, and three (SPX, AFP and ADGRE1) of four hub genes were validated in an independent HCC cohort (n=78). Identification of hub genes for HCC clinical traits has implications for further understanding of the molecular genetic basis of HCC.

Molecular mechanisms of drug resistance in ovarian cancer

Ovarian cancer is the most lethal malignancy among the gynecological cancers, with a 5-year survival rate, mainly due to being diagnosed at advanced stages, recurrence and resistance to the current chemotherapeutic agents. Drug resistance is a complex phenomenon and the number of known involved genes and cross-talks between signaling pathways in this process is growing rapidly. Thus, discovering and understanding the underlying molecular mechanisms involved in chemo-resistance are crucial for management of treatment and identifying novel and effective drug targets as well as drug discovery to improve therapeutic outcomes. In this review, the major and recently identified molecular mechanisms of drug resistance in ovarian cancer from relevant literature have been investigated. In the final section of the paper, new approaches for studying detailed mechanisms of chemo-resistance have been briefly discussed.

Obesity and Ovarian Cancer

Ovarian cancer is the most fatal gynecologic cancer and is an important source of cancer-related mortality, particularly in developed countries. Despite substantial research examining adiposity (primarily adult body mass index [BMI]), the overall evidence suggests only a weak positive association between adiposity and risk of ovarian cancer, with stronger associations observed for population-based case-control studies compared to prospective studies. Ovarian cancer is not one disease and emerging data suggest that higher BMI may only be associated with risk of certain histologic subtypes, including low-grade serous and invasive mucinous tumors. Interestingly, some larger studies and meta-analyses have reported a stronger relationship with premenopausal ovarian cancers, which are more likely to be of these subtypes. Relatively few studies have conducted detailed examinations of other adiposity-related factors such as measures of abdominal adiposity, early-life body size and weight change. While the underlying mechanisms that may relate adiposity to risk are unclear, increased inflammatory biomarkers have been associated with risk and hormonal factors, including androgen levels, may be important for the development of mucinous tumors. Future research should leverage the large sample sizes of consortia to evaluate associations by key tumor characteristics as well as consider patterns of weight change over the life course with both ovarian cancer risk and survival.

Pre-diagnosis diet and survival after a diagnosis of ovarian cancer

Background:

The relationship between diet and survival after ovarian cancer diagnosis is unclear as a result of a limited number of studies and inconsistent findings.

Methods:

We examined the association between pre-diagnostic diet and overall survival in a population-based cohort (n=811) of Australian women diagnosed with invasive epithelial ovarian cancer between 2002 and 2005. Diet was measured by validated food frequency questionnaire. Deaths were ascertained up to 31 August 2014 via medical record review and Australian National Death Index linkage. We conducted Cox proportional hazards regression analysis, controlling for diagnosis age, tumour stage, grade and subtype, residual disease, smoking status, body mass index, physical activity, marital status, and energy intake.

Results:

We observed improved survival with highest compared with lowest quartile of fibre intake (hazard ratio (HR)=0.69, 95% CI: 0.53–0.90, P-trend=0.002). There was a suggestion of better survival for women with highest compared with lowest intake category of green leafy vegetables (HR=0.79, 95% CI: 0.62–0.99), fish (HR=0.74, 95% CI: 0.57–0.95), poly- to mono-unsaturated fat ratio (HR=0.76, 95% CI: 0.59–0.98), and worse survival with higher glycaemic index (HR=1.28, 95% CI: 1.01–1.65, P-trend=0.03).

Conclusions:

The associations we observed between healthy components of diet pre-diagnosis and ovarian cancer survival raise the possibility that dietary choices after diagnosis may improve survival.

Lipid Droplets: A Key Cellular Organelle Associated with Cancer Cell Survival under Normoxia and Hypoxia

The Warburg effect describes the phenomenon by which cancer cells obtain energy from glycolysis even under normoxic (O₂-sufficient) conditions. Tumor tissues are generally exposed to hypoxia owing to inefficient and aberrant vasculature. Cancer cells have multiple molecular mechanisms to adapt to such stress conditions by reprogramming the cellular metabolism. Hypoxia-inducible factors are major transcription factors induced in cancer cells in response to hypoxia that contribute to the metabolic changes. In addition, cancer cells within hypoxic tumor areas have reduced access to serum components such as nutrients and lipids. However, the effect of such serum factor deprivation on cancer cell biology in the context of tumor hypoxia is not fully understood. Cancer cells are lipid-rich under normoxia and hypoxia, leading to the increased generation of a cellular organelle, the lipid droplet (LD). In recent years, the LD-mediated stress response mechanisms of cancer cells have been revealed. This review focuses on the production and functions of LDs in various types of cancer cells in relation to the associated cellular environment factors including tissue oxygenation status and metabolic mechanisms. This information will contribute to the current understanding of how cancer cells adapt to diverse tumor environments to promote their survival.

Near-Infrared Fluorogenic Probes with Polarity-Sensitive Emission for in Vivo Imaging of an Ovarian Cancer Biomarker

Lysophosphatidic acid (LPA, cutoff values ≥ 1.5 μM) is an effective biomarker for early stage ovarian cancer. The development of selective probes for LPA detection is therefore critical for early clinical diagnosis. Although current methods have been developed for the detection of LPA in solution, they cannot be used for tracking LPA in vivo. Here, we report a near-infrared (NIR) fluorescent probe that can selectively respond to LPA based on polarity-sensitive emission at a very low detection limit of 0.5 μM in situ. This probe exhibits a marked increase of fluorescence at 720 nm upon binding to LPA, allowing the direct visualization of LPA in vitro and in vivo without interference from other biomolecules. Moreover, the probe containing two arginine-glycine-aspartic acid units can be efficiently taken up by cancer cells based on an αvβ3 integrin receptor targeting mechanism. It also exhibits excellent biocompatibility and high pH stability in live cells and in vivo. Confocal laser scanning microscopy and flow cytometric imaging of SKOV-3 cells have confirmed that our probe can be used to image LPA in live cells. In particular, its NIR turn-on fluorescence can be used to effectively monitor LPA imaging in a SKOV-3 tumor-bearing mouse model. Our probe may pave the way for the detection of cancer-related biomarkers and even for early stage cancer diagnosis.

Highly-accurate metabolomic detection of early-stage ovarian cancer

High performance mass spectrometry was employed to interrogate the serum metabolome of early-stage ovarian cancer (OC) patients and age-matched control women. The resulting spectral features were used to establish a linear support vector machine (SVM) model of sixteen diagnostic metabolites that are able to identify early-stage OC with 100% accuracy in our patient cohort. The results provide evidence for the importance of lipid and fatty acid metabolism in OC and serve as the foundation of a clinically significant diagnostic test.

Enzyme-instructed self-assembly: a multistep process for potential cancer therapy

The central dogma of the action of current anticancer drugs is that the drug tightly binds to its molecular target for inhibition. The reliance on tight ligand-receptor binding, however, is also the major root of drug resistance in cancer therapy. In this article, we highlight enzyme-instructed self-assembly (EISA)-the integration of enzymatic transformation and molecular self-assembly-as a multistep process for the development of cancer therapy. Using apoptosis as an example, we illustrate that the combination of enzymatic transformation and self-assembly, in fact, is an inherent feature of apoptosis. After the introduction of EISA of small molecules in the context of supramolecular hydrogelation, we describe several key studies to underscore the promises of EISA for developing cancer therapy. Particularly, we will highlight that EISA allows one to develop approaches to target "undruggable" targets or "untargetable" features of cancer cells and provides the opportunity for simultaneously interacting with multiple targets. We envision that EISA, used separately or in combination with current anticancer therapeutics, will ultimately lead to a paradigm shift for developing anticancer medicine that inhibit multiple hallmark capabilities of cancer.

Transketolase is upregulated in metastatic peritoneal implants and promotes ovarian cancer cell proliferation

Ovarian cancer, the most lethal gynaecological cancer, is characterised by the shedding of epithelial cells from the ovarian surface, followed by metastasis and implantation onto the peritoneal surfaces of abdominal organs. Our proteomic studies investigating the interactions between peritoneal (LP-9) and ovarian cancer (OVCAR-5) cells found transketolase (TKT) to be regulated in the co-culture system. This study characterized TKT expression in advanced stage (III/IV) serous ovarian cancers (n = 125 primary and n = 54 peritoneal metastases), normal ovaries (n = 6) and benign serous cystadenomas (n = 10) by immunohistochemistry. In addition, we also evaluated the function of TKT in ovarian cancer cells in vitro. Nuclear TKT was present in all primary serous ovarian cancer tissues examined (median 82.0 %, range 16.5-100 %) and was significantly increased in peritoneal metastases compared with matching primary cancers (P = 0.01, Wilcoxon Rank test). Kaplan-Meier survival and Cox regression analyses showed that high nuclear TKT positivity in peritoneal metastases (>94 %) was significantly associated with reduced overall survival (P = 0.006) and a 2.8 fold increased risk of ovarian cancer death (95 % CI 1.29-5.90, P = 0.009). Knockdown of TKT by siRNAs significantly reduced SKOV-3 cell proliferation but had no effect on their motility or invasion. Oxythiamine, an inhibitor of TKT activity, significantly inhibited the proliferation of four ovarian cancer cell lines (OV-90, SKOV-3, OVCAR-3 and OVCAR-5) and primary serous ovarian cancer cells isolated from patient ascites. In conclusion, these findings indicate that TKT plays an important role in the proliferation of metastatic ovarian cancer cells and could be used as novel therapeutic target for advanced disease.

Pathway crosstalk analysis of microarray gene expression profile in human hepatocellular carcinoma

Liver cancer is the third most common cause of cancer death in the world. Hepatocellular carcinoma (HCC) is the main pathological types in liver cancer, which amounts to 70-85 % of primary liver cancer in the world and 90 % in China. The aim of this study was to establish a PPI network and a pathway crosstalk network to isolate important dysfunctional pathways which play an important role in the pathogenesis of HCC. System biology approach was used in this research. A PPI network was firstly built and then a dysfunctional crosstalk network of HCC related pathways was constructed. Several important significant dysfunctional crosstalk pathways were identified. Basal transcription factors (hsa03022), Glycerophospholipid metabolism (hsa00564) and Metabolism of xenobiotics by cytochrome P450 (hsa00980) were significantly interact with Pathway in cancer (hsa05200). Besides, pathway Axon guidance (hsa04360) was also dysfunctional crosstalk with Pathway in cancer (hsa05200). The crosstalks among these pathways reveal some evidence that the pathways closely cooperated and play important tasks in HCC progression. Besides, the pathway hsa04360 dysfunctional crosstalk with the hsa05200 indicates there would be a same mechanism for HCC invasion and migration.

Fatty acid synthase inhibition engages a novel caspase-2 regulatory mechanism to induce ovarian cancer cell death

Blockade of fatty acid synthase (FASN), a key enzyme involved in de novo lipogenesis, results in robust death of ovarian cancer cells. However, known FASN inhibitors have proven to be poor therapeutic agents due to their ability to induce cachexia. Therefore, we sought to identify additional targets in the pathway linking FASN inhibition and cell death whose modulation might kill ovarian cancer cells without the attendant side effects. Here, we show that the initiator caspase-2 is required for robust death of ovarian cancer cells induced by FASN inhibitors. REDD1 (also known as Rtp801 or DDIT4), a known mTOR inhibitor previously implicated in the response to FASN inhibition, is a novel caspase-2 regulator in this pathway. REDD1 induction is compromised in ovarian cancer cells that do not respond to FASN inhibition. Inhibition of FASN induced an ATF4-dependent transcriptional induction of REDD1; downregulation of REDD1 prevented orlistat-induced activation of caspase-2, as monitored by its cleavage, proteolytic activity, and dimerization. Abrogation of REDD1-mediated suppression of mTOR by TSC2 RNAi protected FASN inhibitor-sensitive ovarian cancer cells (OVCA 420 cells) from orlistat-induced death. Conversely, suppression of mTOR with the chemical inhibitors PP242 or rapamycin sensitized DOV13, an ovarian cancer cell line incapable of inducing REDD1, to orlistat-induced cell death through caspase-2. These findings indicate that REDD1 positively controls caspase-2-dependent cell death of ovarian cancer cells by inhibiting mTOR, placing mTOR as a novel upstream regulator of caspase-2 and supporting the possibility of manipulating mTOR to enhance caspase-2 activation in ovarian cancer.

Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action

BACKGROUND

Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity.

RESULTS

In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors.

CONCLUSION

Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure.

ABCA transporter gene expression and poor outcome in epithelial ovarian cancer

BACKGROUND

ATP-binding cassette (ABC) transporters play various roles in cancer biology and drug resistance, but their association with outcomes in serous epithelial ovarian cancer (EOC) is unknown.

METHODS

The relationship between clinical outcomes and ABC transporter gene expression in two independent cohorts of high-grade serous EOC tumors was assessed with real-time quantitative polymerase chain reaction, analysis of expression microarray data, and immunohistochemistry. Associations between clinical outcomes and ABCA transporter gene single nucleotide polymorphisms were tested in a genome-wide association study. Impact of short interfering RNA-mediated gene suppression was determined by colony forming and migration assays. Association with survival was assessed with Kaplan-Meier analysis and log-rank tests. All statistical tests were two-sided.

RESULTS

Associations with outcome were observed with ABC transporters of the "A" subfamily, but not with multidrug transporters. High-level expression of ABCA1, ABCA6, ABCA8, and ABCA9 in primary tumors was statistically significantly associated with reduced survival in serous ovarian cancer patients. Low levels of ABCA5 and the C-allele of rs536009 were associated with shorter overall survival (hazard ratio for death = 1.50; 95% confidence interval [CI] =1.26 to 1.79; P = 6.5e-6). The combined expression pattern of ABCA1, ABCA5, and either ABCA8 or ABCA9 was associated with particularly poor outcome (mean overall survival in group with adverse ABCA1, ABCA5 and ABCA9 gene expression = 33.2 months, 95% CI = 26.4 to 40.1; vs 55.3 months in the group with favorable ABCA gene expression, 95% CI = 49.8 to 60.8; P = .001), independently of tumor stage or surgical debulking status. Suppression of cholesterol transporter ABCA1 inhibited ovarian cancer cell growth and migration in vitro, and statin treatment reduced ovarian cancer cell migration.

CONCLUSIONS

Expression of ABCA transporters was associated with poor outcome in serous ovarian cancer, implicating lipid trafficking as a potentially important process in EOC.