Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation.

Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R2=0.6586, p=0.0044) and stress granule (a=0.8000, R2=0.6000, p=0.0085) as the most potential star molecule in this field. More interestingly, the Random-Walk-Strategy-based Walktrap algorithm further revealed that "phase separation, cancer, transcription, super-enhancer, epigenetics"(Relevance Percentage[RP]=100%, Development Percentage[DP]=29.2%), "stress granule, immunotherapy, tumor microenvironment, RNA binding protein"(RP=79.2%, DP=33.3%) and "nanoparticle, apoptosis"(RP=70.8%, DP=25.0%) are closely associated with this field, but are still under-developed and worthy of further exploration. In conclusion, this study profiled the global scientific landscape, discovered a crucial emerging research cluster, identified several pivotal research molecules, and predicted several crucial but still under-developed directions that deserve further research, providing an important reference value for subsequent basic and clinical research of phase separation in cancer.

Comparative investigation of neoadjuvant immunotherapy versus adjuvant immunotherapy in perioperative patients with cancer: a global-scale, cross-sectional, large-sample informatics study.

BACKGROUND: Neoadjuvant and adjuvant immunotherapies for cancer have evolved through a series of remarkable and critical research advances; however, addressing their similarities and differences is imperative in clinical practice. Therefore, this study aimed to examine their similarities and differences from the perspective of informatics analysis. METHODS: This cross-sectional study retrospectively analyzed extensive relevant studies published between 2014 and 2023 using stringent search criteria, excluding non-peer-reviewed and non-English documents. The main outcome variables are publication volume, citation volume, connection strength, occurrence frequency, relevance percentage, and development percentage. Furthermore, an integrated comparative analysis was conducted using unsupervised hierarchical clustering, spatiotemporal analysis, regression statistics, and Walktrap algorithm analysis. RESULTS: This analysis included 1,373 relevant studies. Advancements in neoadjuvant and adjuvant immunotherapies have been promising over the last decade, with an annual growth rate of 25.18% vs. 6.52% and global collaboration (International Co-authorships) of 19.93% vs. 19.84%. Respectively, five dominant research clusters were identified through unsupervised hierarchical clustering based on machine learning, among which Cluster 4 (Balance of neoadjuvant immunotherapy efficacy and safety) and Cluster 2 (Adjuvant immunotherapy clinical trials) (Average Publication Year [APY]: 2021.70±0.70 vs. 2017.54±4.59) are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including microsatellite instability (R2=0.7500, P=0.0025) and biomarkers (R2=0.6505, P=0.0086) in neoadjuvant scenarios, and the tumor microenvironment (R2=0.5571, P=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "neoadjuvant immunotherapy, non-small cell lung cancer (NSCLC), immune checkpoint inhibitors, melanoma" and "adjuvant immunotherapy, melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs. 100%, Development Percentage: 37.5% vs. 17.1%) are extremely relevant to this field but remain underdeveloped, highlighting the need for further investigation. CONCLUSION: This study identified pivotal research signatures and provided substantial predictions for neoadjuvant and adjuvant cancer immunotherapies. In addition, comprehensive quantitative comparisons revealed a notable shift in focus within this field, with neoadjuvant immunotherapy taking precedence over adjuvant immunotherapy after 2020; such a qualitative finding facilitate proper decision-making for subsequent research and mitigate the wastage of healthcare resources.

Comprehensive scientometrics and visualization study profiles lymphoma metabolism and identifies its significant research signatures.

Background: There is a wealth of poorly utilized unstructured data on lymphoma metabolism, and scientometrics and visualization study could serve as a robust tool to address this issue. Hence, it was implemented. Methods: After strict quality control, numerous data regarding the lymphoma metabolism were mined, quantified, cleaned, fused, and visualized from documents (n = 2925) limited from 2013 to 2022 using R packages, VOSviewer, and GraphPad Prism. Results: The linear fitting analysis generated functions predicting the annual publication number (y = 31.685x - 63628, R² = 0.93614, Prediction in 2027: 598) and citation number (y = 1363.7x - 2746019, R² = 0.94956, Prediction in 2027: 18201). In the last decade, the most academically performing author, journal, country, and affiliation were Meignan Michel (n = 35), European Journal of Nuclear Medicine and Molecular Imaging (n = 1653), USA (n = 3114), and University of Pennsylvania (n = 86), respectively. The hierarchical clustering based on unsupervised learning further divided research signatures into five clusters, including the basic study cluster (Cluster 1, Total Link Strength [TLS] = 1670, Total Occurrence [TO] = 832) and clinical study cluster (Cluster 3, TLS = 3496, TO = 1328). The timeline distribution indicated that radiomics and artificial intelligence (Cluster 4, Average Publication Year = 2019.39 ± 0.21) is a relatively new research cluster, and more endeavors deserve. Research signature burst and linear regression analysis further confirmed the findings above and revealed additional important results, such as tumor microenvironment (a = 0.6848, R² = 0.5194, p = 0.019) and immunotherapy (a = 1.036, R² = 0.6687, p = 0.004). More interestingly, by performing a "Walktrap" algorithm, the community map indicated that the "apoptosis, metabolism, chemotherapy" (Centrality = 12, Density = 6), "lymphoma, pet/ct, prognosis" (Centrality = 11, Density = 1), and "genotoxicity, mutagenicity" (Centrality = 9, Density = 4) are crucial but still under-explored, illustrating the potentiality of these research signatures in the field of the lymphoma metabolism. Conclusion: This study comprehensively mines valuable information and offers significant predictions about lymphoma metabolism for its clinical and experimental practice.

A scientometrics and visualization analysis of oxidative stress modulator Nrf2 in cancer profiles its characteristics and reveals its association with immune response.

Background: Nrf2, an essential and fascinating transcription factor, enjoys a dual property in the occurrence and development of inflammation and cancer. For over two decades, numerous studies regarding Nrf2 in cancer have been reported, whereas there is still a lack of a scientometrics and visualization analysis of Nrf2 in cancer. Hence, a scientometric study regarding the oxidative stress modulator Nrf2 was implemented. Methods: After the quality screening, we defined 7168 relevant studies from 2000 to 2021. CiteSpace, VOSviewer, R software, and GraphPad Prism were used for the following scientometric study and visualization analysis, including field profiles, research hotspots, and future predictions. Results: The total number of publications and citations are 1058 and 54,690, respectively. After polynomial fitting curve analysis, two prediction functions of the annual publication number (y = 3.3909x2 - 13585x + 1 E+07) and citation number (185.45x2 - 743669x + 7 E+08) were generated. After scientometric analysis, we found that Biochemistry Molecular Biology correlates with Nrf2 in cancer highly, and Free Radical Biology and Medicine is a good choice for submitting Nrf2-related manuscripts. The current research hotspots of Nrf2 in cancer mainly focus on cancer therapy and its cellular and molecular mechanisms. "antioxidant response element (87.5)", "gene expression (43.98)", "antioxidant responsive element (21.14)", "chemoprevention (20.05)", "carcinogenesis (19.2)", "cancer chemoprevention (18.45)", "free radical (17.15)", "response element (14.17)", and "chemopreventive agent (14.04)" are important for cancer therapy study. In addition, "glutathione-S-transferase (47)", "keap1 (15.39)", and "heme oxygenase 1 gene (24.35)" are important for inflammation and cell fate study. More interestingly, by performing an "InfoMap" algorithm, the thematic map showed that the "immune response" is essential to oxidative stress modulator Nrf2 but not well developed, indicating it deserves further exploration. Conclusion: This study revealed field profiles, research hotspots, and future directions of oxidative stress modulator Nrf2 in inflammation and cancer research, and our findings will offer a vigorous roadmap for further studies in this field.

PHB promotes bladder cancer cell epithelial-mesenchymal transition via the Wnt/ß-catenin signaling pathway.

As a member of PHB (prohibitin1) family, PHB plays important roles in many cancers, but its property in bladder carcinoma aggressiveness is unknown. This research was to explore the function and potential mechanism of PHB in bladder carcinoma in vivo and in vitro. The invasive abilities of cancer cell were determined by transwell and wound-healing assays. The function of PHB was confirmed by gene knockdown and overexpression methods. Further in vivo confirmation was performed in a nude mouse model with lung metastasis. The relationship of PHB and ß-catenin was confirmed by immunoprecipitation and immunofluorescence staining assays. The protein expression of epithelial-mescenchymal transition (EMT) and Wnt/ß-catenin signaling pathway was tested by immunofluorescence staining and western blotting assay. The depletion of PHB prevented bladder cancer cell invasiveness and inhibited EMT. Contrarily，the abilities of bladder carcinoma cells migration and invasion in vitro as well as metastasis in vivo were enhanced when the PHB overexpressed unnormally. Importantly, the ß-catenin was identified to be bound by PHB and ß-catenin knockdown reduced the cancer cell migration, invasion and EMT in PHB overexpressing cells. In addition, PHB stabilized ß-catenin by inhibiting its ubiqutin-mediated degradation thus leading to increased Wnt/ß-catenin signaling. These observations indicate that PHB could promote bladder cancer aggressiveness by binding with ß-catenin to prevent the degradation of ß-catenin and the localized invasive bladder cancer patients with PHB overexpression should take more aggressive postsurgical adjuvant anticancer therapies.

The ß-catenin-LINC00183-miR-371b-5p-Smad2/LEF1 axis promotes adult T-cell lymphoblastic lymphoma progression and chemoresistance.

BACKGROUND: High-intensity chemotherapy regimens are often used in adult T-cell lymphoblastic lymphoma (T-LBL) patients. Nevertheless, the response rate remains unsatisfactory due to emergence of chemoresistance. Growing evidence has shown that long non-coding RNAs (lncRNAs) are involved in tumor progression and chemoresistance. Herein, we investigated the potential role of lncRNAs in T-LBLs. METHODS: RNAseq was used to screen and identify candidate lncRNAs associated with T-LBL progression and chemoresistance. Luciferase reporter assay was used to examine the binding of miR-371b-5p to the 3'UTR of Smad2 and LEF1, and the binding of TCF-4/LEF1 to the promoter of LINC00183. Chromatin immunoprecipitation assay was undertaken to analyze the connection between LEF1 and the LINC00183 promoter region. RNA immunoprecipitation assays were used to explore the mechanism whereby LINC00183 regulated miR-371b-5p. MTT and flow cytometry assays were used to measure apoptosis of T-LBL cells. RESULTS: LINC00183 was upregulated in T-LBL progression and chemoresistant tissues in both the Sun Yat-sen University Cancer Center dataset and the First Affiliated Hospital of Anhui Medical University dataset. High expression of LINC00183 was correlated with poorer overall survival and progression-free survival of T-LBL patients compared to those with low expression of LINC00183. Furthermore, miR-371b-5p was negatively regulated by LINC00183. In vivo and in vitro assays showed that LINC00183-mediated T-LBL chemoresistance depended on miR-371b-5p expression. The direct binding of miR-371b-5p to Smad2 and LEF1 was verified by luciferase assays. It was shown that TCF4/LEF1 could bind to the LINC00183 promoter site and increase its transcript level. Downregulation of miR-371b-5p led to increased expression of Smad2/LEF1, and in turn increased LINC00183 expression. Additionally, phospho-Smad2 promotes nuclear translocation of ß-catenin, LINC00183 downregulation decreased chemoresistance induced by ß-catenin and TGF-ß1 in T-LBL cells. CONCLUSION: We unraveled a ß-catenin-LINC00183-miR-371b-5p-Smad2/LEF1 feedback loop that promotes T-LBL progression and chemoresistance, indicating that LINC00183 may serve as a potential therapeutic target in T-LBLs.

Erratum: Acidic Microenvironment Up-Regulates Exosomal miR-21 and miR-10b in Early-Stage Hepatocellular Carcinoma to Promote Cancer Cell Proliferation and Metastasis: Erratum.

[This corrects the article DOI: 10.7150/thno.30958.].

The ß-catenin/TCF-4-LINC01278-miR-1258-Smad2/3 axis promotes hepatocellular carcinoma metastasis.

Hepatocellular carcinoma (HCC) metastasis is largely responsible for HCC-associated recurrence and mortality. We aimed to identify metastasis-related long non-coding RNAs (lncRNAs) to understand the molecular mechanism of HCC metastasis. We first identified that miR-1258 was downregulated in HCC tissues both in The Cancer Genome Atlas (TCGA) and Sun Yat-sen University Cancer Center (SYSUCC) dataset. MiR-1258 expression negatively correlated with recurrence-free survival and overall survival of HCC patients. MiR-1258 overexpression inhibited migration and invasion of HCC cells both in vitro and in vivo, whereas miR-1258 downregulation promoted cell metastasis. Luciferase assays verified direct binding of miR-1258 to Smad2 and Smad3, thereby attenuating TGF-ß/Smad signaling. We further established that lncRNA LINC01278 was a negative regulator of miR-1258. In vivo and in vitro assays demonstrated that LINC01278-mediated HCC metastasis was dependent on miR-1258 expression. Furthermore, miR-1258 downregulation in turn increased LINC01278 expression. We also observed that TCF-4 could bind to the LINC01278 promoter site. In addition, LINC01278 downregulation decreased migration and invasion of HCC cells induced by ß-catenin and TGF-ß1 both in vitro and in vivo. We uncovered a novel mechanism for ß-catenin/TCF-4-LINC01278-miR-1258-Smad2/3 feedback loop activation in HCC metastasis, and the study indicated that LINC01278 could serve as a therapeutic target for HCC metastasis.

A CpG Methylation Classifier to Predict Relapse in Adults with T-Cell Lymphoblastic Lymphoma.

PURPOSE: Adults with T-cell lymphoblastic lymphoma (T-LBL) generally benefit from treatment with acute lymphoblastic leukemia (ALL)-like regimens, but approximately 40% will relapse after such treatment. We evaluated the value of CpG methylation in predicting relapse for adults with T-LBL treated with ALL-like regimens. EXPERIMENTAL DESIGN: A total of 549 adults with T-LBL from 27 medical centers were included in the analysis. Using the Illumina Methylation 850K Beadchip, 44 relapse-related CpGs were identified from 49 T-LBL samples by two algorithms: least absolute shrinkage and selector operation (LASSO) and support vector machine-recursive feature elimination (SVM-RFE). We built a four-CpG classifier using LASSO Cox regression based on association between the methylation level of CpGs and relapse-free survival in the training cohort (n = 160). The four-CpG classifier was validated in the internal testing cohort (n = 68) and independent validation cohort (n = 321). RESULTS: The four-CpG-based classifier discriminated patients with T-LBL at high risk of relapse in the training cohort from those at low risk (P < 0.001). This classifier also showed good predictive value in the internal testing cohort (P < 0.001) and the independent validation cohort (P < 0.001). A nomogram incorporating five independent prognostic factors including the CpG-based classifier, lactate dehydrogenase levels, Eastern Cooperative Oncology Group performance status, central nervous system involvement, and NOTCH1/FBXW7 status showed a significantly higher predictive accuracy than each single variable. Stratification into different subgroups by the nomogram helped identify the subset of patients who most benefited from more intensive chemotherapy and/or sequential hematopoietic stem cell transplantation. CONCLUSIONS: Our four-CpG-based classifier could predict disease relapse in patients with T-LBL, and could be used to guide treatment decision.

A gene-expression-based signature predicts survival in adults with T-cell lymphoblastic lymphoma: a multicenter study.

We aimed to establish a discriminative gene-expression-based classifier to predict survival outcomes of T-cell lymphoblastic lymphoma (T-LBL) patients. After exploring global gene-expression profiles of progressive (n = 22) vs. progression-free (n = 28) T-LBL patients, 43 differentially expressed mRNAs were identified. Then an eleven-gene-based classifier was established using LASSO Cox regression based on NanoString quantification. In the training cohort (n = 169), high-risk patients stratified using the classifier had significantly lower progression-free survival (PFS: hazards ratio 4.123, 95% CI 2.565-6.628; p < 0.001), disease-free survival (DFS: HR 3.148, 95% CI 1.857-5.339; p < 0.001), and overall survival (OS: HR 3.790, 95% CI 2.237-6.423; p < 0.001) compared with low-risk patients. The prognostic accuracy of the classifier was validated in the internal testing (n = 84) and independent validation cohorts (n = 360). A prognostic nomogram consisting of five independent variables including the classifier, lactate dehydrogenase levels, ECOG-PS, central nervous system involvement, and NOTCH1/FBXW7 status showed significantly greater prognostic accuracy than each single variable alone. The addition of a five-miRNA-based signature further enhanced the accuracy of this nomogram. Furthermore, patients with a nomogram score ≥154.2 significantly benefited from the BFM protocol. In conclusion, our nomogram comprising the 11-gene-based classifier may make contributions to individual prognosis prediction and treatment decision-making.

Acidic Microenvironment Up-Regulates Exosomal miR-21 and miR-10b in Early-Stage Hepatocellular Carcinoma to Promote Cancer Cell Proliferation and Metastasis.

Rationale: The incidence of hepatocellular carcinoma is rising worldwide. It is predicted that nearly half of the early-stage hepatocellular carcinoma (E-HCC) patients will develop recurrence. Dysregulated pH, a hallmark of E-HCC, is correlated with poor prognosis. The acidic microenvironment has been shown to promote the release of exosomes, the membrane vesicles recognized as intercellular communicators associated with tumor progression, recurrence, and metastasis. We, therefore, aimed to identify exosomes induced by acidic microenvironment that may regulate E-HCC progression and to explore their mechanisms and clinical significance in E-HCCs. Methods: miRNA microarray analysis and LASSO logistic statistic model were used to identify the main functional exosomal miRNAs. Invasion and scratch assays were performed to examine the migration and invasion of HCC cells. Immunoblotting and immunofluorescence were employed to detect the epithelial-to-mesenchymal transition (EMT) in HCC cells. Chromatin immunoprecipitation (ChIP) was used to analyze the binding of HIF-1α and HIF-2α to promoter regions of miR-21 and miR-10b. Results: The acidic microenvironment in HCC was correlated with poor prognosis of patients. Exosomes from HCC cells cultured in the acidic medium could promote cell proliferation, migration, and invasion of recipient HCC cells. We identified miR-21 and miR-10b as the most important functional miRNAs in acidic HCC-derived exosomes. Also, the acidic microenvironment triggered the activation of HIF-1α and HIF-2α and stimulated exosomal miR-21 and miR-10b expression substantially promoting HCC cell proliferation, migration, and invasion both in vivo and in vitro. In E-HCC patients, serum exosomal miR-21 and miR-10b levels were associated with advanced tumor stage and HIF-1α and HIF-2α expression and were independent prognostic factors for disease-free survival of E-HCC patients. Most importantly, we developed a nano-drug to target exosomal miR-21 and/or miR-10b and examined its therapeutic effects against HCC in vivo. Conclusion: Our findings suggested that the exosomal miR-21 and miR-10b induced by acidic microenvironment in HCC promote cancer cell proliferation and metastasis and may serve as prognostic molecular markers and therapeutic targets for HCC.

Prognostic and predictive value of a microRNA signature in adults with T-cell lymphoblastic lymphoma.

New prognostic factors are needed to establish indications for haematopoietic stem cell transplantation (HSCT) in first complete remission (CR1) for T-cell lymphoblastic lymphoma (T-LBL) patients. We used microarray to compare T-LBL tissue samples (n = 75) and fetal thymus tissues (n = 20), and identified 35 differentially expressed miRNAs. Using 107 subjects as the training group, we developed a five-miRNA-based classifier to predict patient survival with LASSO Cox regression: lower risk was associated with better prognosis (disease-free survival (DFS): hazard ratio (HR) 4.548, 95% CI 2.433-8.499, p < 0.001; overall survival (OS): HR 5.030, 95% CI 2.407-10.513, p < 0.001). This classifier displayed good performance in the internal testing set (n = 106) and the independent external set (n = 304). High risk was associated with more favorable response to HSCT (DFS: HR 1.675, 95% CI 1.127-2.488, p = 0.011; OS: HR 1.602, 95% CI 1.055-2.433, p = 0.027). When combined with ECOG-PS and/or NOTCH1/FBXW7 status, this classifier had even better prognostic performance in patients receiving HSCT (DFS: HR 2.088, 95% CI 1.290-3.379, p = 0.003; OS: HR 1.996, 95% CI 1.203-3.311, p = 0.007). The five-miRNA classifier may be a useful prognostic biomarker for T-LBL adults, and could identify subjects who could benefit from HSCT.

Genetic profile and biological implication of PIN2/TRF1-interacting telomerase inhibitor 1 (PinX1) in human cancers: an analysis using The Cancer Genome Atlas.

Pin2/TRF1-interacting telomere inhibitor 1 (PinX1) was originally identified as a telomerase inhibitor, involved in maintaining telomerase activity, telomere length, and chromosomal stability. However, research has shown that PinX1 can have opposing molecular status in its expression patterns in several other tumor types. We thus investigated the genetic profile and biological implication of PinX1 in several human cancers using the cBioportal database. Our results showed that PinX1 deletion accounted for the most alterations, with the frequency of its deletion regularly occurring in pathological types of carcinosarcoma and adenocarcinoma. We found few instances of PinX1 gene mutations and 3D structural analysis demonstrated that these mutation sites were always located within telomerase inhibitor domains. Furthermore, our analysis of several human cancers from the cBioportal database revealed more frequent PinX1 homozygous depletion and PinX1 heterozygous deficiency, but both more infrequent PinX1 gain and rare instances of PinX1 amplification. The status of PinX1 genetic alterations was correlated with prognosis and may be tumor-type specific. As such, its biological function in tumorigenesis and later prognosis is complicated and may involve co-worked with NEIL2, R3HCC1, POLR3D, GTF2E2, and INTS10. In addition, we observed that PinX1 interacts with TERT, DKC1, PTGES3, and HSP90AA1. PinX1 mRNA expression was decreased in most selected cancer tissues, which could promote tumor growth and enhance tumorigenicity. Collectively, our data reveal PinX1 expression patterns and potential mechanisms in various human cancers. Further work will be needed to comprehensively examine its role in tumor genesis and progression.

The depletion of PinX1 involved in the tumorigenesis of non-small cell lung cancer promotes cell proliferation via p15/cyclin D1 pathway.

BACKGROUND: The telomerase/telomere interacting protein PinX1 has been suggested as a tumor suppressor. However, the clinical and biological significance of PinX1 in human non-small cell lung cancer (NSCLC) is unclear. METHODS: PinX1 gene/expression pattern and its association with NSCLC patient survival were analyzed in cBioportal Web resource and two cohorts of NSCLC samples. A series of in vivo and in vitro assays were performed to elucidate the function of PinX1 on NSCLC cells proliferation and underlying mechanisms. RESULTS: More frequency of gene PinX1 homozygous deletion and heterozygote deficiency was first retrieved from cBioportal Web resource. Low expression of PinX1 correlated with smoking condition, histological type, T stage, N stage, M stage and TNM stage, and was an independent predictor for overall survival in a learning cohort (n = 93) and a validation cohort (n = 51) of NSCLC patients. Furthermore, knockdown of PinX1 dramatically accelerated NSCLC cell proliferation and G1/S transition, whereas ectopic overexpression of PinX1 substantially inhibited cell viability and cell cycle transition in vitro and in vivo. p15/cyclin D1 pathway and BMP5 might contribute to PinX1-associated cell proliferation and cell cycle transition. CONCLUSION: The cost-effective expression of PinX1 could constitute a novel molecular predictor/marker for NSCLC management.

[Analysis of environmental factors and polycystic ovary syndrome].

OBJECTIVE: To investigate environmental risk factors associated with polycystic ovary syndrome (PCOS). METHODS: A retrospective study was carried out from Feb 2005 to Apr 2006. A total of 108 cases with PCOS and 108 patients without PCOS (control group) were interviewed using a designed questionnaire. RESULTS: Univariate analysis of environmental factors indicated that risk factors related to PCOS were: occupation, education, disposable plastic cup for drinking, cooking oil fume and indoor decoration, all of which were significantly related to PCOS (P < 0.05). Multi-variate analysis confirmed that the risk factors associated with PCOS were disposable plastic cup for drinking, cooking oil fume and indoor decoration (P value: 0.011, 0.012, 0.026, 0.011, OR value: 2.800, 3.027, 2.370, 2.478). CONCLUSIONS: PCOS is related to environmental endocrine-disrupting chemicals.