Largest Cause Of Cancer Deaths Research Articles

Chemoinformatics and machine learning techniques to identify novel inhibitors of the lemur tyrosine kinase-3 receptor involved in breast cancer.

Breast cancer is still the largest cause of cancer death in women, and around 70% of primary breast cancer patients are estrogen receptor (ER)-positive, which is the most frequent kind of breast cancer. The lemur tyrosine kinase-3 (LMTK3) receptor has been linked to estrogen responsiveness in breast cancer. However, the function of LMTK3 in reaction to cytotoxic chemotherapy has yet to be studied. Breast cancer therapy research remains tricky due to a paucity of structural investigations on LMTK3. We performed structural investigations on LMTK3 using molecular docking and molecular dynamics (MD) simulations of the LMTK3 receptor in complex with the top three inhibitor molecules along with a control inhibitor. Analysis revealed the top three compounds show the best binding affinities during docking simulations. Interactive analysis of hydrogen bonds inferred hotspot residues Tyr163, Asn138, Asp133, Tyr56, Glu52, Ser132, Asp313, and Asp151. Some other residues in the 5-Å region determined strong alkyl bonds and conventional hydrogen bond linkages. Furthermore, protein dynamics analysis revealed significant modifications among the top complexes and the control system. There was a transition from a loop to a-helix conformation in the protein-top1 complex, and in contrast, in complexes top2 and top3, the formation of a stabilizing sheet in the C chain was observed, which limited significant mobility and increased complex stability. Significant structural alterations were observed in the protein-top complexes, including a shorter helix region and the creation of some loop regions in comparison to the control system. Interestingly, binding free energies, including MMGB/PBSA WaterSwap analysis estimation, reveals that the top1 complex system was more stable than other systems, especially in comparison to the control inhibitor complex system. These results suggest a the plausible mode of action for the novel inhibitors. Therefore, the current investigation contributes to understanding the mechanism of action, serving as a basis for future experimental studies.

Chronic treatment with TNF-α, alone and in combination with Takinib, SB203580 and metformin induce cell death in breast cancer

Breast cancer (BC) is the most common malignancy, and the largest cause of cancer death among women. The interactions between tumor cells and tumor micro environmental factors have a major impact on tumor progression. One of the critical pro-inflammatory cytokines present in breast cancer tumor microenvironment is TNF-α. The aim of this study was to evaluate the long-term effect of TNF-α (1 week) along with p38 or TAK1 inhibitors as well as metformin on induction of cellular death, cancer stem cell and expression of metastatic marker CXCR4. MCF-7 and MDA-MB-231 cells were treated with TNF-α for one week and then were treated with combination of Takinib, SB203580 or Metformin; after all treatments were done, cell proliferation, cellular death, surface expression of CXCR4, CD44 and CD24 were determined. The results showed that treatment with TNF-α alone or in combination with Takinib, SB203580 and metformin elevated induction of cellular death in both cell lines compared to the control group. TNF-α also increased CXCR4 expression in MCF-7 cells, but it reduced its expression in the MDA-MB-231 cells. Also, breast cancer stem cells (BCSCs) population decreased in MDA-MB-231 cells treated with TNF-α alone or in combination with SB203580 and metformin. Although, in MCF-7 cells only combination of TNF-α and Takinib reduced BCSCs population in a time dependent manner. Altogether, we showed that TNF-α alone or in combination with other treatments can affect the progression of breast cancer.

Comprehensive analysis of the significance of METTL7A gene in the prognosis of lung adenocarcinoma.

The most common subtype of lung cancer, called lung adenocarcinoma (LUAD), is also the largest cause of cancer death in the world. The aim of this study was to determine the importance of the METTL7A gene in the prognosis of patients with LUAD. This particular study used a total of four different LUAD datasets, namely TCGA-LUAD, GSE32863, GSE31210 and GSE13213. Using RT-qPCR, we were able to determine METTL7A expression levels in clinical samples. Univariate and multivariate Cox regression analyses were used to identify factors with independent effects on prognosis in patients with LUAD, and nomograms were designed to predict survival in these patients. Using gene set variation analysis (GSVA), we investigated differences in enriched pathways between METTL7A high and low expression groups. Microenvironmental cell population counter (MCP-counter) and single-sample gene set enrichment analysis (ssGSEA) methods were used to study immune infiltration in LUAD samples. Using the ESTIMATE technique, we were able to determine the immune score, stromal score, and estimated score for each LUAD patient. A competing endogenous RNA network, also known as ceRNA, was established with the help of the Cytoscape program. We detected that METTL7A was down-regulated in pan-cancer, including LUAD. The survival study indicates that METTL7A was a protective factor in the prognosis of LUAD. The univariate and multivariate Cox regression analyses revealed that METTL7A was a robust independent prognostic indicator in survival prediction. Through the use of GSVA, several immune-related pathways were shown to be enriched in both the high-expression and low-expression groups of METTL7A. Analysis of the tumor microenvironment revealed that the immune microenvironment of the group with low expression was suppressed, which may be connected to the poor prognosis. To explore the ceRNA regulatory mechanism of METTL7A, we finally constructed a regulatory network containing 1 mRNA, 2 miRNAs, and 5 long non-coding RNAs (lncRNAs). In conclusion, we presented METTL7A as a potential and promising prognostic indicator of LUAD. This biomarker has the potential to offer us with a comprehensive perspective of the prediction of prognosis and treatment for LUAD patients.

Factors Affecting the Outcome of the Operable Subtype Luminal B Breast Cancer Treatment

Breast cancer is a condition of uncontrolled breast cell proliferation that most frequently develops from the ductal epithelial cells (85%) or lobules (15%) of the breast glands. Poor prognoses for patients can result from cancer's extensive organ metastasis, now the second largest cause of cancer death in women. This study aims to identify the variables that affect how well patients with the operable breast cancer subtype Luminal B respond to treatment at RSUP DR M Djamil Padang. This research used a cross-sectional methodology with a retrospective study approach to identify characteristics that affect the treatment outcome for operable breast cancer subtype luminal B at RSUP DR. M. Djamil Padang. From August to November 2022, the study was carried out in the Oncology Surgery Division of RSUP DR. M. Djamil Padang. With HER2 being the main component, multivariate analysis revealed that HER2 and the kind of therapy were significantly connected with the treatment outcome for cancer patients.

Improve the Colorectal Cancer Diagnosis Using Gut Microbiome Data.

In the United States, colorectal cancer is the second largest cause of cancer death, and accurate early detection and identification of high-risk patients is a high priority. Although fecal screening tests are available, the close relationship between colorectal cancer and the gut microbiome has generated considerable interest. We describe a machine learning method for gut microbiome data to assist in diagnosing colorectal cancer. Our methodology integrates feature engineering, mediation analysis, statistical modeling, and network analysis into a novel unified pipeline. Simulation results illustrate the value of the method in comparison to existing methods. For predicting colorectal cancer in two real datasets, this pipeline showed an 8.7% higher prediction accuracy and 13% higher area under the receiver operator characteristic curve than other published work. Additionally, the approach highlights important colorectal cancer-related taxa for prioritization, such as high levels of Bacteroides fragilis, which can help elucidate disease pathology. Our algorithms and approach can be widely applied for Colorectal cancer prediction using either 16 S rRNA or shotgun metagenomics data.

Peritoneal Modulators of Endometriosis-Associated Ovarian Cancer.

Ovarian cancer is the 4th largest cause of cancer death in women. Approximately 10–15% of women of childbearing age suffer from endometriosis. Endometriosis is defined by the growth and presence of endometrial tissue (lesions) outside of the uterus. The women with endometriosis also have an increased presence of peritoneal fluid (PF) that comprises of inflammatory cells, growth factors, cytokines/chemokines, etc. Epidemiological studies have shown that >3% of women with endometriosis develop ovarian cancer (low-grade serous or endometrioid types). Our hypothesis is that the PF from women with endometriosis induces transformative changes in the ovarian cells, leading to ovarian cancer development. PF from women with and without endometriosis was collected after IRB approval and patient consent. IOSE (human normal ovarian epithelial cells) and TOV-21G cells (human ovarian clear cell carcinoma cell line) were treated with various volumes of PF (no endometriosis or endometriosis) for 48 or 96 h and proliferation measured. Expression levels of epigenetic regulators and FoxP3, an inflammatory tumor suppressor, were determined. A Human Cancer Inflammation and Immunity Crosstalk RT2 Profiler PCR array was used to measure changes in cancer related genes in treated cells. Results showed increased growth of TOV-21G cells treated with PF from women with endometriosis versus without endometriosis and compared to IOSE cells. Endo PF treatment induced EZH2, H3K27me3, and FoxP3. The RT2 PCR array of TOV-21G cells treated with endo PF showed upregulation of various inflammatory genes (TLRs, Myd88, etc.). These studies indicate that PF from women with endometriosis can both proliferate and transform ovarian cells and hence this microenvironment plays a major mechanistic role in the progression of endometriosis to ovarian cancer.

Non-Coding RNA Polymorphisms (rs2910164 and rs1333049) Associated With Prognosis of Lung Cancer Under Platinum-Based Chemotherapy.

Purpose: Lung cancer is the largest cause of cancer deaths in the world. Platinum-based chemotherapy is a foundation of first-line chemotherapy. However, the prognosis of lung cancer treated with platinum-based chemotherapy is still a challenge. Single nucleotide polymorphism of non-coding RNA has the potential to be a biomarker, but its effectiveness has yet to be comprehensively assessed. In this study, we explored the association between polymorphisms of non-coding RNA and prognosis of lung cancer patients receiving platinum-based chemotherapy.Materials and Methods: For 446 lung cancer patients receiving platinum-based chemotherapy, 22 single nucleotide polymorphisms of microRNA and long noncoding RNA were genotyped by MALDI-TOF mass spectrometry. Cox regression analysis, Kaplan-Meier method, and long-rank test have been performed to assess the association of overall and progression-free survival with polymorphisms.Results: In the additive and dominant models, genetic polymorphism of ANRIL rs1333049 (G > C) was significantly associated with progression-free survival. Additive model: CC vs GC vs GG [HR = 0.84, p = 0.021, 95% CI (0.73–0.97)]; Recessive model: CC vs GG + GC [HR = 0.77, p = 0.026, 95% CI (0.61–0.97)]. In the dominant model, compared with the CC genotype patients, lower risk of death [HR = 0.81, p = 0.036, 95% CI (0.66–0.99)] and lower risk of progression [HR = 0.81, p = 0.040, 95% CI (0.67–0.99)] have been observed on the patients with CG or GG genotype in miR-146A rs2910164.Conclusion: Our research demonstrated the potential of using ANRIL rs1333049 (G > C) and miR-146A rs2910164 (C > G) as biomarkers to support the prediction of a better prognosis for lung cancer patients receiving platinum-based chemotherapy.

The role of HOMER3 in liver cancer progression.

89 Background: Liver cancer (LC) is in the seventh most common cancer and the fourth largest cause of cancer deaths. Although significant progress has been made in the prevention and treatment of viral hepatitis; alcoholic liver disease, obesity and diabetes are now emerging as major causes for LC. Recently there has been increase in identification of biomarkers which can predict LC risk and disease progression, but the roles of HOMER3 gene in LC are not known. Methods: First the expression of HOMER3 between normal and tumor tissues was determined using The Cancer Genome Atlas (TCGA), Genetic Expression Omnibus (GEO) and protein atlas datasets. HOMER3 expression at different clinical stage and overall survival (OS) was also determined. The role of HOMER3 on OS in relation to cancer stage, hepatitis virus infection and alcohol intake was also determined. STRING database determined HOMER3 interaction network and TCGA was used to verify the correlation status, and the roles of the network genes on OS. The pathways enriched by HOMER3 were determined by Gene Set Enrichment Analysis (GSEA). Results: HOMER3 was significantly highly expressed in tumor tissues as compared to normal tissues. The expression of HOMER3 correlated positively with clinical stage, with highest expression in advanced stages (Stage 3 and 4), and high HOMER3 expression was associated with poor OS. HOMER3’ s high expression was associated with poor OS in advanced stage, alcohol intake, and in those negative of viral hepatitis infection. HOMER3 interacted with HOMER1, SHANK1, GRM5, GRM1, DLGAP1, SHANK2, DLG4, SHANK3, DLG2 and DLGAP4, with positive correlation to HOMER1, SHANK1, GRM5, GRM1, DLGAP1, DLG4 and DLGAP4 and negative correlation to SHANK2, SHANK3 and DLG2. HOMER1 and DLGAP4 high expression were associated with poor OS while SHANK2, SHANK3 and DLG2 high expression were associated with favorable OS. GRM5 and GRM1 high expression were associated with favorable OS despite being positively correlated with HOMER3. ECM receptor interaction and Notch signaling were the upregulated pathways while Metabolism of xenobiotics by cytochrome p450 and PPAR signaling were the downregulated pathways. Conclusions: HOMER3 may is have a role in liver cancer progression of which its targeting may improve LC outcome.

Abstract P6-02-12: Artificial Intelligence over thermal images for radiation-free breast cancer screening

Abstract Introduction: Breast cancer is the largest cause of cancer deaths in women today. NIRAMAI has developed a novel solution for detecting early stage breast cancer in women of all age groups. It is low cost, non-contact and portable solution. This radiation-free solution also works on dense breasts and hence is applicable beyond developing countries. The core of the solution is a Computer Aided Diagnostics engine called Thermalytix, which uses Artificial Intelligence algorithms on high resolution thermal images. In this paper, we present a comparative analysis of Thermalytix solution with Mammography, the standard screening modality, in a retrospective trial that was conducted across 3 reputed cancer hospitals in India. Aim: To compare the sensitivity, specificity, NPV and PPV of Thermalytix with Mammography. Methods: A multisite comparative study was performed on 194 patients across 3 reputed cancer hospitals in India with informed consent from subjects and ethics committee approval of respective hospitals. Every person who was going for a mammography test was made to undergo the non-invasive Thermalytix test prior to mammography examination. As per standard of care in India, all women who had a suspicious lesion in Mammo was sent to Ultrasound and then biopsy. 93 of the 194 subjects enrolled were found to be malignant by this standard procedure (9 of them did not have a biopsy report). Niramai Thermaytix test gave the automated reports detecting patients with suspected malignancy and those results were compared with ground truth derived from mammography, sono-mammography and biopsy. In a similar manner, standalone mammography observation was compared with the above ground truth to compare the two modalities as individual modalities. Results: Out of the 194 subjects, 93 positive cases and Niramai accurately detected 91 cases and called out one as boundary case. Sensitivity of Thermalytix was 98% and NPV was 97%, while sensitivity of Mammography was 94% with an NPV of 94%. NIRAMAI Thermalytix detected 4 more malignant patients compared to Mammography. On the other hand, mammography scored over Thermalytix in PPV and Specificity by 10%. These results are tabulated at Comparing NIRAMAI Thermalytix with Mammography NIRAMAIMammographySensitivity98%94%Specificity76%89%PPV79%89%NPV97%94%Accuracy87%91%Number of subjects = 194 high risk patients Among the 194 patients, 39 women were found to have dense breasts and 19 with heterogenous dense breasts – on whom ultrasound and elastography was performed by the Radiologist to correlate with mammography results and make the final observations. Niramai test alone was effective in these patients. The results show that Thermalytix is an emerging, radiation-free diagnostic modality that has comparable accuracy to Mammography. We conclude that NIRAMAI Thermalytix can be complementary modality to mammography as it works well on women of all age groups, including women with dense breasts. Its higher sensitivity and NPV adds to its potential to be the first screening test for early detection of breast cancer. Citation Format: Manjunath G, Sudhakar S, Kakileti S, Madhu H, Singh A. Artificial Intelligence over thermal images for radiation-free breast cancer screening [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P6-02-12.

Outcomes and Treatment Patterns in Patients with Oligometastatic Non-Small Cell Lung Cancer (NSCLC) Diagnosed at Craniotomy: A Single Institution Study

NSCLC remains the largest cause of cancer death in the US and more than two-thirds of patients have either locally advanced or metastatic disease at diagnosis, including a large subset who present with symptomatic intracranial metastases. Historically, such patients had a uniformly poor prognosis, but in recent years, those with oligometastatic disease are increasingly being evaluated for thoracic consolidative radiation therapy (T-RT) due to the improvement in systemic therapies and prolonged progression-free survival (PFS). We retrospectively reviewed a cohort of patients with NSCLC who were diagnosed at craniotomy to establish a pathologic diagnosis and palliate symptoms. We assessed the types of treatments offered, PFS, overall survival (OS), and factors influencing outcome. A neurosurgical database of patients undergoing craniotomy in 2014-2015 was filtered to include those diagnosed with NSCLC at the time of that surgery and underwent further treatment at our institution. Medical records were reviewed for demographics, descriptors of the intracranial and extracranial burden of disease, systemic therapies, radiation therapy courses, PFS, and OS. Descriptive statistics were computed and 95% confidence intervals (CI) were constructed for Kaplan-Meier median survival estimates. Summary statistics were computed for factors associated with receipt of T-RT. Of 104 patients identified, 67 patients met inclusion criteria with available clinical information. Median age at time of presentation was 64 (range: 28-92). Median KPS was 80. Median number of brain metastases was 2 (range: 1-24), with a median volume of largest brain metastasis of 19cc (range: 1-75). WBRT was utilized for 38 patients (56.7%), while 28 (41.8%) had radiosurgery to the craniotomy cavity and other sites of intracranial disease. Two patients (3.8%) went straight to systemic therapy. Consolidative T-RT was used in 28 patients (41.8%); criteria for T-RT use were not pre-specified. Median PFS in patients who did and did not receive T-RT was 8.0 and 2.3 months, respectively (p<0.01). Median OS in patients who did and did not receive T-RT was 17.9 months and 4.3 months, respectively (p<0.01). Factors associated with T-RT receipt included higher KPS (p<0.01) and receipt of SRS for brain lesions (p=0.03). Patients presenting with intracranial metastases from NSCLC who are candidates for craniotomy appear to have prolonged OS as compared to historical benchmarks. In our cohort, consolidation T-RT was associated with prolonged survival. Although assignment of patients to T-RT in this retrospective cohort was not based on pre-specified criteria and might have been related to unknown bias, the hypothesis that T-RT improves OS in patients with oligometastatic disease should be further tested in prospective clinical trials.

Pathway-based discovery of genetic interactions in breast cancer.

Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions.

PTH-283 Presentation and referral pathway for colorectal cancer patients: is national screening programme and 2 week wait making a difference?

Introduction Colorectal cancer is the second largest cause of cancer death in the UK, and survival is significantly improved when diagnosed at an early stage; thus the call for earlier detection and faster referral. However, there are concerns that many cancers are still left undetected. This cross-sectional study aims to explore variations in the presentation and referral pathway for colorectal cancer patients in a district general hospital. Method Data from 388 histologically proven colorectal cancer patients diagnosed between 1stJanuary 2012 and 31stDecember 2014 were analysed, and the method of presentation was reviewed. For patients presenting as elective admissions, their referral pathway was further analysed to establish the impact of faster referral methods, including 2 week wait and National Screening Programme. This was reviewed against the 4,950 patients referred to the trust as 2 week wait in the same time period. Finally, MDT outcomes were quantitatively analysed to explore the reasons why patients did not undergo surgical intervention for their cancer. Results Of the 388 colorectal cancer patients, 34.3% (n = 133) presented through 2 week wait, 8.7% (n = 34) were referred through National Screening; 17.3% (n = 67) elective patients presented as routine. Of all the colorectal patients 32.7% (n = 123) patients were still presenting through emergency admissions. Of the 4,950 patients who presented via 2 week wait in the 36 months analysed, only 2.7% (n = 133) had a positive cancer diagnosis. Quantitative analysis of management showed that of the 388 colorectal cancer patients, 53.4% (n = 207) underwent surgical resection as part of their management. Of the 181 patients who did not undergo surgical resection, 65.7% were due to the advanced stage of the cancer on presentation, and 21.9% were due to patient factors including co-morbidities and patient refusal. Conclusion Whilst the number of patients with colorectal cancer presenting through faster referral methods is high, the percentage of positive 2 week wait referrals is very low; and a worrying amount of patients are still presenting through emergency admissions. Furthermore, there are large amounts of patients presenting who do not undergo surgical intervention. Overall this would suggest that despite the 2 week wait and National Screening Programme, many patients are presenting late with cancer, or indeed being missed all together in the community. Disclosure of interest None Declared.

Breast Cancer Classification: Comparative Performance Analysis of Image Shape-Based Features and Microarray Gene Expression Data

Recently, there has been greater attention to the use of classifier systems in medical diagnosis. Medical diagnostic tools provide automated procedures for objective decisions by making use of quantitative measures and machine learning techniques. These tools are effective and helpful for medical experts to diagnose diseases. One of such diseases is breast cancer which is the second largest cause of cancer deaths among women. To build an intelligent tool, it is very important to have an effective set of features. Two types of feature sets have been commonly implemented for the purpose of breast cancer diagnosis: image shape-based features and microarray gene expression data. Both types of feature sets have been widely implemented; however, there has been no work that directly compared the classification performance of these two feature sets. In this paper, we intensively review related works that used both types of feature sets and we also review the implemented machine learning algorithms. Moreover, we run extensive experiments to compare the classification performance of the aforementioned feature sets. Our results show that the image shape-based features are more discriminative for breast cancer classification when tested with ten-fold cross validation. To check the robustness of the best performing feature set, we further examine it with five-fold cross validation and with a variety of generative classification algorithms.

Decomposing socio-economic inequality in colorectal cancer screening uptake in England

Colorectal cancer (CRC) is the second largest cause of cancer death in the UK. Since 2010, CRC screening based on Faecal Occult Blood testing has been offered by the NHS in England biennially to all persons age 60–69 years. Several studies have demonstrated a gradient in uptake using area-level markers of socio-economic status (SES), but few have examined the individual-level contributors to the gradient. We aimed to quantify the extent of SES inequality in CRC screening uptake in England using individual-level data, and to identify individual factors associated with this inequality.We used data from 1833 participants (aged 61–69) in Wave 5 (collected in years 2010/11) of the English Longitudinal Study of Ageing (ELSA) eligible for having been sent at least one CRC screening invitation. Uptake was defined by self-report of ever having been screened as part of the National Screening Programme. We assessed socio-economic inequality using the corrected concentration index of uptake against SES rank, which was derived by regressing a range of SES markers against net non-pension household wealth. Other demographic and health-related variables were included in the analysis. Factors associated with inequality were measured using concentration index decomposition.There was a significant pro-rich gradient in screening uptake (concentration index: 0.16, 95% CI:0.11–0.22), mostly explained within our model by differences in non-pension wealth (38.7%), partner screening status (15.9%), sickness/disability (13.5%), and health literacy (8.5%).Interventions aimed at reducing inequalities in CRC screening uptake should focus on improving acceptability of screening in populations with low levels of education and literacy barriers.

Smoking-attributable cancer mortality in NSW, Australia, 1972-2008.

To estimate the impact of smoking-attributable cancer mortality on trends in cancer mortality in New South Wales (NSW), Australia, between 1972 and 2008. The study is a retrospective analysis of cancer mortality in NSW using NSW Central Cancer Registry data. Smoking-attributable cancer deaths were estimated using the smoking impact ratio method, which provides an indirect estimate of exposure to tobacco in the NSW population using lung cancer mortality. Trends in age-standardised cancer mortality rates by cancer type and the number of years of life lost due to smoking-attributable cancer deaths were estimated. In NSW, the cancer mortality rate decreased in males by 26% and females by 19% between 1989 and 2008. Nearly half (44%) of the decrease for males was a result of the decline in smoking-attributable cancer deaths. Despite a decline in the female all-cancer mortality rate, the smoking-attributable cancer mortality rate increased from 20.3 per 100 000 to 26.8 per 100 000 between 1989 and 2008. Smoking-attributable cancer deaths in women increased from around 150 per year in the early 1970s to 1186 in 2008; for men, the number remained stable at just over 2000 deaths per year since the 1980s. Although the lung cancer mortality rate declined in men, lung cancer remains the largest cause of cancer death. Lung cancer has overtaken breast cancer to be the largest cause of cancer death among women, with 17.1% (n = 998) of cancer deaths due to lung cancer in 2008. Despite declining all-cancer mortality in NSW, around 3330 cancer deaths in 2008 were due to the accumulated hazard of smoking in current and ex-smokers. This highlights the importance of tobacco control as part of a comprehensive cancer control plan.

DNA-Based Vaccine Is More Efficient than Non-Pathogenic Live Vaccine for the Prevention of HPV16 E7-Overexpressing Cancers

Introduction: Vaccinology provides promising approaches for the control of various infectious diseases. Among different strategies, DNA vaccines offer attractive research opportunities for development of vaccines for induction of antigen-specific immunity owing to their stability, simplicity of delivery, safety and cost effec tiveness. However, there is a need to increase their potency by the use of adjuvants such as glycoprotein 96 and electroporation delivery. On the other hand, the attenuated or non-pathogenic live vectors have been used to deliver DNA into cells as efficient delivery tools in gene therapy. Recently, a non-pathogenic protozoan, Leishmania tarentolae (L. tar), has attracted attention as an in situ protein-delivery vehicle. Cervical cancer is the second largest cause of cancer deaths among women worldwide and human papillomaviruses (HPV) is reportedly a frequent cause of this type of cancer. Methods: In the current study, we compared the potential of live L. tarbased and DNA-based vaccines expressing HPV16 E7 linked to C-terminal fragment of gp96 in a tumor mouse model. Results: We found that subcutaneous DNA injection with E7-CT (gp96), followed by electroporation, generate a significant E7-specific IFN- γ immune response and in vivo protective effects compared to transgenic L. tar-E7-CT (gp96) in challenge experiments with TC-1. Conclusion: It could be concluded that the DNA vaccine showed higher efficacy compared to the non-pathogenic live parasite-based vaccine in the tumor mice model. Vac Res, 2014, 1 (1): 21 - 24

Ezrin expression and cell survival regulation in colorectal cancer

Colorectal cancer (CRC) is the second largest cause of cancer deaths in the United States. A key barrier that prevents better outcomes for this type of cancer as well as other solid tumors is the lack of effective therapies against the metastatic disease. Thus there is an urgent need to fill this gap in cancer therapy. We utilized a 2D-DIGE proteomics approach to identify and characterize proteins that are differentially regulated between primary colon tumor and liver metastatic deposits of the IGF1R-dependent GEO human CRC xenograft, orthotopically implanted in athymic nude mice that may serve as potential therapeutic targets against CRC metastasis. We observed increased expression of ezrin in liver metastasis in comparison to the primary colonic tumor. Increased ezrin expression was further confirmed by western blot and microarray analyses. Ezrin, a cytoskeletal protein belonging to Ezrin–Radixin–Moesin (ERM) family plays important roles in cell motility, invasion and metastasis. However, its exact function in colorectal cancer is not well characterized. Establishment of advanced GEO cell lines with enhanced liver-metastasizing ability showed a significant increase in ezrin expression in liver metastasis. Increased phosphorylation of ezrin at the T567 site (termed here as p-ezrin T567) was observed in liver metastasis. IHC studies of human CRC patient specimens showed an increased expression of p-ezrin T567 in liver metastasis compared to the primary tumors of the same patient. Ezrin modulation by siRNA, inhibitors and T567A/D point mutations significantly downregulated inhibitors of apoptosis (IAP) proteins XIAP and survivin that have been linked to increased aberrant cell survival and metastasis and increased cell death. Inhibition of the IGF1R signaling pathway by humanized recombinant IGF1R monoclonal antibody MK-0646 in athymic mouse subcutaneous xenografts resulted in inhibition of p-ezrin T567 indicating ezrin signaling is downstream of the IGF1R signaling pathway. We identified increased expression of p-ezrin T567 in CRC liver metastasis in both orthotopically implanted GEO tumors as well as human patient specimens. We report for the first time that p-ezrin T567 is downstream of the IGF1R signaling and demonstrate that ezrin regulates cell survival through survivin/XIAP modulation.

Fuzzy Analysis of Breast Cancer Disease using Fuzzy c-means and Pattern Recognition

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. The automatic diagnosis of breast cancer is an important, real-world medical problem. In this article is introduced a new approach for diagnosis of breast cancer. The proposed approach uses Fuzzy c-means (FCM) algorithm and pattern recognition method. Algorithm has been applied to breast cancer clinic instances obtained from the University of Wisconsin. Using FCM algorithm clinic instances are grouped into two clusters, one with benign instances and other with malign instances. Further, input data are divided in train data and test data and success of each is evaluated. In pattern recognition method each input test data is assigned to one of the clusters obtained from the process of FCM classification. The proposed system has showed that the recommended system has a high accuracy.

Chemoprevention of pancreatic cancer using solid-lipid nanoparticulate delivery of a novel aspirin, curcumin and sulforaphane drug combination regimen

Pancreatic cancer is the fourth largest cause of cancer deaths in the Unites States and the prognosis is grim with <5% survival chances upon diagnosis. The objective of this study was to assess the combined chemopreventive effect of solid lipid nanoparticle (SLN) encapsulated drugs aspirin (ASP), curcumin (CUR) and free sulforaphane (SFN) for the chemoprevention of pancreatic cancer. Experiments were carried out (1) to evaluate the feasibility of encapsulation of these chemopreventive agents within solid lipid systems and (2) to measure the synergistic effects of a combination of ASP with CUR in SLNs mixed with free SFN against cell proliferation and apoptosis in pancreatic cancer cells, MIA PaCa-2 and Panc-1. The SLNs were prepared using a modified solvent evaporation technique and were characterized for particle sizing, encapsulation efficiency and drug release. ASP and CUR SLNs were formulated within the particle size range of 150–250 nm and were found to have an encapsulation efficiency of 85 and 69%, respectively. Sustained release of drugs over a 96 h period from SLNs was observed. The SLNs were stable over a 3-month storage period at room temperature. Cell viability studies demonstrated that combinations of low doses of ASP SLN (25 μM), CUR SLN (2.5 μM) and free SFN (5 μM) significantly reduced cell viability by 43.6 and 48.49% in MIAPaca-2 and Panc-1 cell lines, respectively. Furthermore, increased apoptosis of 61.3 and 60.37% was found in MIA Paca-2 and Panc-1 cell lines, respectively, in comparison to the individual doses administered. Synergistic effects were demonstrated using MTS and apoptosis assays. Thus, this study successfully demonstrated the feasibility of using a solid lipid nanoparticulate system for the first time to deliver this novel combination chemoprevention regimen, providing valuable evidence for the usability of nanotechnology-based drug regimens towards pancreatic cancer chemoprevention.

Breast Cancer Recognition Using a Novel Hybrid Intelligent Method

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. This paper presents a novel hybrid intelligent method for recognition of breast cancer tumors. The proposed method includes three main modules: the feature extraction module, the classifier module, and the optimization module. In the feature extraction module, fuzzy features are proposed as the efficient characteristic of the patterns. In the classifier module, because of the promising generalization capability of support vector machines (SVM), a SVM-based classifier is proposed. In support vector machine training, the hyperparameters have very important roles for its recognition accuracy. Therefore, in the optimization module, the bees algorithm (BA) is proposed for selecting appropriate parameters of the classifier. The proposed system is tested on Wisconsin Breast Cancer database and simulation results show that the recommended system has a high accuracy.