Novel Strategies for the Early Detection and Prevention of Lung Cancer

A GAN-based method for 3D lung tumor reconstruction boosted by a knowledge transfer approach

Three-dimensional (3D) image reconstruction of tumors has been one of the most effective techniques for accurately visualizing tumor structures and treatment with high resolution, which requires a set of two-dimensional medical images such as CT slices. In this paper we propose a novel method based on generative adversarial networks (GANs) for 3D lung tumor reconstruction by CT images. The proposed method consists of three stages: lung segmentation, tumor segmentation and 3D lung tumor reconstruction. Lung and tumor segmentation are performed using snake optimization and Gustafson-Kessel (GK) clustering. In the 3D reconstruction part first, features are extracted using the pre-trained VGG model from the tumors that detected in 2D CT slices. Then, a sequence of extracted features is fed into an LSTM to output compressed features. Finally, the compressed feature is used as input for GAN, where the generator is responsible for high-level reconstructing the 3D image of the lung tumor. The main novelty of this paper is the use of GAN to reconstruct a 3D lung tumor model for the first time, to the best of our knowledge. Also, we used knowledge transfer to extract features from 2D images to speed up the training process. The results obtained from the proposed model on the LUNA dataset showed better results than state of the art. According to HD and ED metrics, the proposed method has the lowest values ​​of 3.02 and 1.06, respectively, as compared to those of other methods. The experimental results show that the proposed method performs better than previous similar methods and it is useful to help practitioners in the treatment process.

Cancer incidence and mortality rates and trends in Trinidad and Tobago

BACKGROUND

Cancer is the second leading cause of death in the Caribbean, including the islands of Trinidad and Tobago (TT). The population of TT consists of over 1.3 million people with diverse ancestral and sociocultural backgrounds, both of which may influence cancer incidence and mortality. The objective of this study was to examine incidence and mortality patterns and trends in TT.

METHODS

Cancer surveillance data on 29,512 incident cancer cases reported to the Dr. Elizabeth Quamina Cancer Registry (population-based cancer registry of TT) between 1995 and 2009 were analyzed. Age-standardized rates, overall and by sex, ancestry, and geography, were reported.

RESULTS

The highest incidence and mortality rates were observed for cancers related to reproductive organs in women, namely, breast, cervical, and uterine cancers, and prostate, lung and colorectal cancers among men. Average incidence rates were highest in areas covered by the Tobago Regional Health Authority (TRHA) (188 per 100,000), while average mortality rates were highest in areas covered by the North West Regional Health Authority (108 per 100,000). Nationals of African ancestry exhibited the highest rates of cancer incidence (243 per 100,000) and mortality (156 per 100,000) compared to their counterparts who were of East Indian (incidence, 125 per 100,000; mortality, 66 per 100,000) or mixed ancestry (incidence, 119 per 100,000; mortality, 66 per 100,000).

CONCLUSIONS

Our findings highlight the need for national investment to improve the understanding of the epidemiology of cancer in Trinidad and Tobago, and to ultimately guide much needed cancer prevention and control initiatives in the near future.

CT characteristics of non-small cell lung cancer with epidermal growth factor receptor mutation: a systematic review and meta-analysis

Background

To systematically investigate the relationship between CT morphological features and the presence of epidermal growth factor receptor (EGFR) mutations in non-small cell lung cancer (NSCLC).

Methods

All studies about the CT morphological features of NSCLC with EGFR mutations published between January 1, 2000 and March 15, 2015 were searched in the PubMed and EMBASE databases. Qualified studies were selected according to inclusion criteria. The frequency of EGFR mutations and CT features of ground-glass opacity (GGO) content, tumor size, cavitation, air-bronchogram, lobulation, and spiculation were extracted. The relationship between EGFR mutations and each of these CT features was tested based upon the weighted mean difference or inverse variance in the form of an odds ratio at a 95% confidence interval using Forest Plots. The publication bias was examined using Egger’s test.

Results

A total of 13 studies, consisting of 2146 NSCLC patients, were included, and 51.12% (1097/2146) of patients had EGFR mutations. The EGFR mutations were present in NSCLC with part-solid GGO in contrast to nonsolid GGO (OR = 0.49, 95% CI = 0.25–0.96, P = 0.04). Other CT features such as tumor size, cavitation, air-bronchogram, lobulation and spiculation did not demonstrate statistically significant correlation with EGFR mutations individually (P = 0.91; 0.67; 0.12; 0.45; and 0.36, respectively). No publication bias among the selected studies was noted in this meta-analysis (Egger’s tests, P > 0.05 for all).

Conclusion

This meta-analysis demonstrated that NSCLC with CT morphological features of part-solid GGO tended to be EGFR mutated, which might provide an important clue for the correct selection of patients treated with molecular targeted therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12880-016-0175-3) contains supplementary material, which is available to authorized users.

Serum tumor-associated autoantibodies as diagnostic biomarkers for lung cancer: A systematic review and meta-analysis

OBJECTIVE

We performed a comprehensive review and meta-analysis to evaluate the diagnostic values of serum single and multiplex tumor-associated autoantibodies (TAAbs) in patients with lung cancer (LC).

METHODS

We searched the MEDLINE and EMBASE databases for relevant studies investigating serum TAAbs for the diagnosis of LC. The primary outcomes included sensitivity, specificity and accuracy of the test.

RESULTS

The systematic review and meta-analysis included 31 articles with single autoantibody and 39 with multiplex autoantibodies. Enzyme-linked immunosorbent assay (ELISA) was the most common detection method. For the diagnosis of patients with all stages and early-stage LC, different single or combinations of TAAbs demonstrated different diagnostic values. Although individual TAAbs showed low diagnostic sensitivity, the combination of multiplex autoantibodies offered relatively high sensitivity. For the meta-analysis of a same panel of autoantibodies in patients at all stages of LC, the pooled results of the panel of 6 TAAbs (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2) were: sensitivity 38% (95% CI 0.35-0.40), specificity 89% (95% CI 0.86-0.91), diagnostic accuracy 65.9% (range 62.5-81.8%), AUC 0.52 (0.48-0.57), while the summary estimates of 7 TAAbs (p53, CAGE, NY-ESO-1, GBU4-5, SOX2, MAGE A4 and Hu-D) were: sensitivity 47% (95% CI 0.34-0.60), specificity 90% (95% CI 0.89-0.92), diagnostic accuracy 78.4% (range 67.5-88.8%), AUC 0.90 (0.87-0.93). For the meta-analysis of the same panel of autoantibodies in patients at early-stage of LC, the sensitivities of both panels of 7 TAAbs and 6 TAAbs were 40% and 29.7%, while their specificities were 91% and 87%, respectively.

CONCLUSIONS

Serum single or combinations of multiplex autoantibodies can be used as a tool for the diagnosis of LC patients at all stages or early-stage, but the combination of multiplex autoantibodies shows a higher detection capacity; the diagnostic value of the panel of 7 TAAbs is higher than the panel of 6 TAAbs, which may be used as potential biomarkers for the early detection of LC.

Volumes Learned: It Takes More Than Size to "Size Up" Pulmonary Lesions

RATIONALE AND OBJECTIVES

This study aimed to review the current understanding and capabilities regarding use of imaging for noninvasive lesion characterization and its relationship to lung cancer screening and treatment.

MATERIALS AND METHODS

Our review of the state of the art was broken down into questions about the different lung cancer image phenotypes being characterized, the role of imaging and requirements for increasing its value with respect to increasing diagnostic confidence and quantitative assessment, and a review of the current capabilities with respect to those needs.

RESULTS

The preponderance of the literature has so far been focused on the measurement of lesion size, with increasing contributions being made to determine the formal performance of scanners, measurement tools, and human operators in terms of bias and variability. Concurrently, an increasing number of investigators are reporting utility and predictive value of measures other than size, and sensitivity and specificity is being reported. Relatively little has been documented on quantitative measurement of non-size features with corresponding estimation of measurement performance and reproducibility.

CONCLUSIONS

The weight of the evidence suggests characterization of pulmonary lesions built on quantitative measures adds value to the screening for, and treatment of, lung cancer. Advanced image analysis techniques may identify patterns or biomarkers not readily assessed by eye and may also facilitate management of multidimensional imaging data in such a way as to efficiently integrate it into the clinical workflow.

Plasma metabolite profiling and chemometric analyses of lung cancer along with three controls through gas chromatography-mass spectrometry

Lung cancer has been the most common death causing cancer in the world for several decades. This study is focused on the metabolite profiling of plasma from lung cancer (LC) patients with three control groups including healthy non-smoker (NS), smokers (S) and chronic obstructive pulmonary disease patients (COPD) samples using gas chromatography-mass spectrometry (GC-MS) in order to identify the comparative and distinguishing metabolite pattern for lung cancer. Metabolites obtained were identified through National Institute of Standards and Technology (NIST) mass spectral (Wiley registry) and Fiehn Retention Time Lock (RTL) libraries. Mass Profiler Professional (MPP) Software was used for the alignment and for all the statistical analysis. 32 out of 1,877 aligned metabolites were significantly distinguished among three controls and lung cancer using p-value ≤ 0.001. Partial Least Square Discriminant Analysis (PLSDA) model was generated using statistically significant metabolites which on external validation provide high sensitivity (100%) and specificity (78.6%). Elevated level of fatty acids, glucose and acids were observed in lung cancer in comparison with control groups apparently due to enhanced glycolysis, gluconeogenesis, lipogenesis and acidosis, indicating the metabolic signature for lung cancer.

Early detection of NSCLC with scFv selected against IgM autoantibody

Survival of patients with lung cancer could be significantly prolonged should the disease be diagnosed early. Growing evidence indicates that the immune response in the form of autoantibodies to developing cancer is present before clinical presentation. We used a phage-displayed antibody library to select for recombinant scFvs that specifically bind to lung cancer-associated IgM autoantibodies. We selected for scFv recombinant antibodies reactive with circulating IgM autoantibodies found in the serum of patients with early stage lung adenocarcinoma but not matched controls. Discriminatory performance of 6 selected scFvs was validated in an independent set of serum from stage 1 adenocarcinoma and matching control groups using two independent novel methods developed for this application. The panel of 6 selected scFvs predicted cancer based on seroreactivity value with sensitivity of 0.8 and specificity of 0.87. Receiver Operative Characteristic curve (ROC) for combined 6 scFv has an AUC of 0.88 (95%CI, 0.76–1.0) as determined by fluorometric microvolume assay technology (FMAT) The ROC curve generated using a homogeneous bridging Mesa Scale Discovery (MSD) assay had an AUC of 0.72 (95% CI, 0.59–0.85). The panel of all 6 antibodies demonstrated better discriminative power than any single scFv alone. The scFv panel also demonstrated the association between a high score - based on seroreactivity - with poor survival. Selected scFvs were able to recognize lung cancer associated IgM autoantibodies in patient serum as early as 21 months before the clinical presentation of disease. The panel of antibodies discovered represents a potential unique non-invasive molecular tool to detect an immune response specific to lung adenocarcinoma at an early stage of disease.

Multiple marker detection in peripheral blood for NSCLC diagnosis

Background

Non-invasive early detection of lung cancer could reduce the number of patients diagnosed with advanced disease, which is associated with a poor prognosis. We analyzed the diagnostic accuracy of a panel of peripheral blood markers in detecting non small cell lung cancer (NSCLC).

Methods

100 healthy donors and 100 patients with NSCLC were enrolled onto this study. Free circulating DNA, circulating mRNA expression of peptidylarginine deiminase type 4 (PAD4/PADI4), pro-platelet basic protein (PPBP) and haptoglobin were evaluated using a Real-Time PCR-based method.

Results

Free circulating DNA, PADI4, PPBP and haptoglobin levels were significantly higher in NSCLC patients than in healthy donors (p<0.0001, p<0.0001, p = 0.0002 and p = 0.0001, respectively). The fitted logistic regression model demonstrated a significant direct association between marker expression and lung cancer risk. The odds ratios of individual markers were 6.93 (95% CI 4.15–11.58; p<0.0001) for free DNA, 6.99 (95% CI 3.75–13.03; p<0.0001) for PADI4, 2.85 (95% CI 1.71–4.75; p<0.0001) for PPBP and 1.16 (95% CI 1.01–1.33; p = 0.031) for haptoglobin. Free DNA in combination with PPBP and PADI4 gave an area under the ROC curve of 0.93, 95% CI = 0.90–0.97, with sensitivity and specificity over 90%.

Conclusions

Free circulating DNA analysis combined with PPBP and PADI4 expression determination appears to accurately discriminate between healthy donors and NSCLC patients. This non-invasive multimarker approach warrants further research to assess its potential role in the diagnostic or screening workup of subjects with suspected lung cancer.

Lung cancer in women

Recent biological advances in tumor research provide clear evidence that lung cancer in females is different from that in males. These differences appear to have a direct impact on the clinical presentation, histology, and outcomes of lung cancer. Women are more likely to present with lung adenocarcinoma, tend to receive a diagnosis at an earlier age, and are more likely to be diagnosed with localized disease. Women may also be more predisposed to molecular aberrations resulting from the carcinogenic effects of tobacco, but do not appear to be more susceptible than men to developing lung cancer. The gender differences found in female lung cancer make it mandatory that gender stratification is used in clinical trials in order to improve the survival rates of patients with lung cancer.

An epigenetic marker panel for detection of lung cancer using cell-free serum DNA

PURPOSE

We investigated the feasibility of detecting aberrant DNA methylation of some novel and known genes in the serum of lung cancer patients.

EXPERIMENTAL DESIGN

To determine the analytic sensitivity, we examined the tumor and the matched serum DNA for aberrant methylation of 15 gene promoters from 10 patients with primary lung tumors by using quantitative methylation-specific PCR. We then tested this 15-gene set to identify the more useful DNA methylation changes in the serum of a limited number of lung cancer patients and controls. In an independent set, we tested the six most promising genes (APC, CDH1, MGMT, DCC, RASSF1A, and AIM1) for further elucidation of the diagnostic application of this panel of markers.

RESULTS

Promoter hypermethylation of at least one of the genes studied was detected in all 10 lung primary tumors. In majority of cases, aberrant methylation in serum DNA was accompanied by methylation in the matched tumor samples. In the independent set, using a single gene that had 100% specificity (DCC), 35.5% (95% CI: 25-47) of the 76 lung cancer patients were correctly identified. For patients without methylated DCC, addition of a logistic regression score that was based on the five remaining genes improved sensitivity from 35.5% to 75% (95% CI: 64-84) but decreased the specificity from 100% to 73% (95% CI: 54-88).

CONCLUSION

This approach needs to be evaluated in a larger test set to determine the role of this gene set in early detection and surveillance of lung cancer.

[Overexpression of IL-8 and MMP-9 confer high malignant phenotype in patients with non-small cell lung cancer]

背景与目的

白细胞介素-8（interleukin-8, IL-8）曾被认为是一种具有趋化作用的炎症因子，近年的研究认为它和基质金属蛋白酶-9（matrix metalloproteinase-9, MMP-9）均为与肿瘤生长和转移密切相关的细胞因子，本研究通过检测IL-8、MMP-9在非小细胞肺癌患者组织和血清中的表达，研究二者与临床病理特征之间的联系，分析肺癌组织和血清中IL-8、MMP-9表达的相关性，并探讨IL-8、MMP-9作为肿瘤标志物评估非小细胞肺癌患者病情进展程度的效能。

方法

应用酶联免疫吸附实验（enzyme-linked immunosorbent assay, ELISA）检测141例非小细胞肺癌患者、40例健康人和40例肺良性疾病患者血清中IL-8、MMP-9的水平。采用免疫组化SP法检测95例非小细胞肺癌、21例良性疾病肺组织及25例正常肺组织中IL-8和MMP-9的表达。

结果

IL-8、MMP-9在非小细胞肺癌患者血清和组织的表达水平明显高于肺良性疾病对照组和健康对照组，其差异有统计学意义，且随着临床病理分期的升高而升高。在肺癌患者组织和血清中，IL-8与淋巴转移均有较强的相关性，在肺癌组织中IL-8和MMP-9的表达具有很强的相关性（r=0.765）。

结论

IL-8、MMP-9表达水平与非小细胞肺癌的进展密切相关，特别是IL-8与肺癌的淋巴转移具有明显的相关性，其机制可能是通过上调MMP-9实现的。

A multi-analyte serum test for the detection of non-small cell lung cancer

BACKGROUND

In this study, we appraised a wide assortment of biomarkers previously shown to have diagnostic or prognostic value for non-small cell lung cancer (NSCLC) with the intent of establishing a multi-analyte serum test capable of identifying patients with lung cancer.

METHODS

Circulating levels of 47 biomarkers were evaluated against patient cohorts consisting of 90 NSCLC and 43 non-cancer controls using commercial immunoassays. Multivariate statistical methods were used on all biomarkers achieving statistical relevance to define an optimised panel of diagnostic biomarkers for NSCLC. The resulting biomarkers were fashioned into a classification algorithm and validated against serum from a second patient cohort.

RESULTS

A total of 14 analytes achieved statistical relevance upon evaluation. Multivariate statistical methods then identified a panel of six biomarkers (tumour necrosis factor-α, CYFRA 21-1, interleukin-1ra, matrix metalloproteinase-2, monocyte chemotactic protein-1 and sE-selectin) as being the most efficacious for diagnosing early stage NSCLC. When tested against a second patient cohort, the panel successfully classified 75 of 88 patients.

CONCLUSIONS

Here, we report the development of a serum algorithm with high specificity for classifying patients with NSCLC against cohorts of various 'high-risk' individuals. A high rate of false positives was observed within the cohort in which patients had non-neoplastic lung nodules, possibly as a consequence of the inflammatory nature of these conditions.

New biomarkers for lung cancer

IMPORTANCE OF THE FIELD

Despite many efforts to improve early detection, lung cancer remains the leading cause of cancer deaths. Stage is the main determinant of prognosis and the basis for deciding treatment options. Screening tests for lung cancer have not been successful so far.

AREAS COVERED IN THE REVIEW

The article reviews the available literature related to biomarkers in use at present and those that could be used for early diagnosis, staging, prognosis, response to therapy and prediction of recurrence. The single biomarkers are analysed, divided according to the technological methods used and the locations of sampling.

WHAT THE READER WILL GAIN

The reader will gain knowledge on biomarkers in use and those now under study. The reader will also gain insights into the difficulties pertaining to the development of biomarkers, results reproducibility and clinical application.

TAKE HOME MESSAGE

Although some markers seem to be promising, at present there is no consensus on the proven value of their clinical use in lung cancer. The future lies probably in a panel of biomarkers instead of individual assays, or in predictive models derived from the integration of clinical variables and gene expression profiles.

Joint registration and segmentation of serial lung CT images for image-guided lung cancer diagnosis and therapy

In image-guided diagnosis and treatment of small peripheral lung lesions the alignment of the pre-procedural lung CT images and the intra-procedural images is an important step to accurately guide and monitor the interventional procedure. Registering the serial images often relies on correct segmentation of the images and, on the other hand, the segmentation results can be further improved by temporal alignment of the serial images. This paper presents a joint serial image registration and segmentation algorithm. In this algorithm, serial images are segmented based on the current deformations, and the deformations among the serial images are iteratively refined based on the updated segmentation results. No temporal smoothness about the deformation fields is enforced so that the algorithm can tolerate larger or discontinuous temporal changes that often appear during image-guided therapy. Physical procedure models could also be incorporated to our framework to better handle the temporal changes of the serial images during intervention. In experiments, we apply the proposed algorithm to align serial lung CT images. Results using both simulated and clinical images show that the new algorithm is more robust compared to the method that only uses deformable registration.

The reversal of drug-resistance in tumors using a drug-carrying nanoparticular system

Medical applications of nanoparticular systems have attracted considerable attention because of their potential use in therapeutic targeting of disease tissues and their lower level of toxicity against healthy tissue, relative to traditional pharmaceutical drugs. The use of nanoparticular systems has been shown to overcome the limitations of most anticancer drugs in clinical applications. In particular, the improved performance of smarted nanoparticular system for solving the drug resistance problems that typically interrupt tumor treatment has provided a promising strategy for successful tumor chemotherapy. This review highlights recent studies that have examined the therapeutic effect of nanoparticular systems on drug-resistant tumors and presents insight on how they work.

Recurrent genomic gains in preinvasive lesions as a biomarker of risk for lung cancer

Lung carcinoma development is accompanied by field changes that may have diagnostic significance. We have previously shown the importance of chromosomal aneusomy in lung cancer progression. Here, we tested whether genomic gains in six specific loci, TP63 on 3q28, EGFR on 7p12, MYC on 8q24, 5p15.2, and centromeric regions for chromosomes 3 (CEP3) and 6 (CEP6), may provide further value in the prediction of lung cancer. Bronchial biopsy specimens were obtained by LIFE bronchoscopy from 70 subjects (27 with prevalent lung cancers and 43 individuals without lung cancer). Twenty six biopsies were read as moderate dysplasia, 21 as severe dysplasia and 23 as carcinoma in situ (CIS). Four-micron paraffin sections were submitted to a 4-target FISH assay (LAVysion, Abbott Molecular) and reprobed for TP63 and CEP 3 sequences. Spot counts were obtained in 30-50 nuclei per specimen for each probe. Increased gene copy number in 4 of the 6 probes was associated with increased risk of being diagnosed with lung cancer both in unadjusted analyses (odds ratio = 11, p<0.05) and adjusted for histology grade (odds ratio = 17, p<0.05). The most informative 4 probes were TP63, MYC, CEP3 and CEP6. The combination of these 4 probes offered a sensitivity of 82% for lung cancer and a specificity of 58%. These results indicate that specific cytogenetic alterations present in preinvasive lung lesions are closely associated with the diagnosis of lung cancer and may therefore have value in assessing lung cancer risk.

Proteome informatics for cancer research: from molecules to clinic

Proteomics offers the most direct approach to understand disease and its molecular biomarkers. Biomarkers denote the biological states of tissues, cells, or body fluids that are useful for disease detection and classification. Clinical proteomics is used for early disease detection, molecular diagnosis of disease, identification and formulation of therapies, and disease monitoring and prognostics. Bioinformatics tools are essential for converting raw proteomics data into knowledge and subsequently into useful applications. These tools are used for the collection, processing, analysis, and interpretation of the vast amounts of proteomics data. Management, analysis, and interpretation of large quantities of raw and processed data require a combination of various informatics technologies such as databases, sequence comparison, predictive models, and statistical tools. We have demonstrated the utility of bioinformatics in clinical proteomics through the analysis of the cancer antigen survivin and its suitability as a target for cancer immunotherapy.

Cancer screening of healthy volunteers using whole-body 18F-FDG-PET scans: The Nishidai clinic study

In order to evaluate the diagnostic performance of cancer screening using whole-body (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) scanning for asymptomatic subjects, we conducted a historical cohort study. The study group comprised 5807 individuals who underwent PET scanning from 2002 to 2003. Each subject had carried out a procedure with whole-body (18)F-FDG-PET scan with some other diagnostic tests. Out of 5807 participants, data from 4881 subjects were analysed. Among them, PET screening revealed abnormal FDG uptake in 562 subjects, and possible or probable malignancy in 324 subjects, and histological diagnosis of cancer in 36 subjects (16 thyroid, seven colon, four lung, five breast, two prostate, and two others) out of them. The overall cancer detection rate was 0.7%, and PET scanning had a sensitivity of 70.6% and a specificity of 94.0%. This result warrants further prospective cohort studies to evaluate the usefulness of PET cancer screening for cancer prevention.

TAT peptide-based micelle system for potential active targeting of anti-cancer agents to acidic solid tumors

A novel drug targeting system for acidic solid tumors has been developed based on ultra pH-sensitive polymer and cell penetrating TAT. The delivery system consisted of two components: 1) A polymeric micelle that has a hydrophobic core made of poly(l-lactic acid) (PLLA) and a hydrophilic shell consisting of polyethylene glycol (PEG) conjugated to TAT (TAT micelle), 2) an ultra pH-sensitive diblock copolymer of poly(methacryloyl sulfadimethoxine) (PSD) and PEG (PSD-b-PEG). The anionic PSD is complexed with cationic TAT of the micelles to achieve the final carrier, which could systemically shield the micelles and expose them at slightly acidic tumor pH. TAT micelles had particle sizes between 20 and 45 nm and their critical micelle concentrations were 3.5 mg/l to 5.5 mg/l. The TAT micelles, upon mixing with pH-sensitive PSD-b-PEG, showed a slight increase in particle size between pH 8.0 and 6.8 (60-90 nm), indicating complexation. As the pH was decreased (pH 6.6 to 6.0) two populations were observed, one that of normal TAT micelles (45 nm) and the other of aggregated hydrophobic PSD-b-PEG. Zeta potential measurements showed similar trend substantiating the shielding/deshielding process. Flow cytometry and confocal microscopy showed significantly higher uptake of TAT micelles at pH 6.6 compared to pH 7.4 indicating shielding at normal pH and deshielding at tumor pH. The confocal microscopy indicated that the TAT not only translocates into the cells but is also seen on the surface of the nucleus. These results strongly indicate that the above micelles would be able to target any hydrophobic drug near the nucleus.

Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues

Successful treatment of multiple cancer types requires early detection and identification of reliable biomarkers present in specific cancer tissues. To test the feasibility of identifying proteins from archival cancer tissues, we have developed a methodology, termed direct tissue proteomics (DTP), which can be used to identify proteins directly from formalin-fixed paraffin-embedded prostate cancer tissue samples. Using minute prostate biopsy sections, we demonstrate the identification of 428 prostate-expressed proteins using the shotgun method. Because the DTP method is not quantitative, we employed the absolute quantification method and demonstrate picogram level quantification of prostate-specific antigen. In depth bioinformatics analysis of these expressed proteins affords the categorization of metabolic pathways that may be important for distinct stages of prostate carcinogenesis. Furthermore, we validate Wnt-3 as an upregulated protein in cancerous prostate cells by immunohistochemistry. We propose that this general strategy provides a roadmap for successful identification of critical molecular targets of multiple cancer types.

Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world

Efforts to reduce global cancer disparities begin with an understanding of geographic patterns in cancer incidence, mortality, and prevalence. Using the GLOBOCAN (2002) and Cancer Incidence in Five Continents databases, we describe overall cancer incidence, mortality, and prevalence, age-adjusted temporal trends, and age-specific incidence patterns in selected geographic regions of the world. For the eight most common malignancies-cancers of lung, breast, colon and rectum, stomach, prostate, liver, cervix, and esophagus-the most important risk factors, cancer prevention and control measures are briefly reviewed. In 2002, an estimated 11 million new cancer cases and 7 million cancer deaths were reported worldwide; nearly 25 million persons were living with cancer. Among the eight most common cancers, global disparities in cancer incidence, mortality, and prevalence are evident, likely due to complex interactions of nonmodifiable (ie, genetic susceptibility and aging) and modifiable risk factors (ie, tobacco, infectious agents, diet, and physical activity). Indeed, when risk factors among populations are intertwined with differences in individual behaviors, cultural beliefs and practices, socioeconomic conditions, and health care systems, global cancer disparities are inevitable. For the eight most common cancers, priorities for reducing cancer disparities are discussed.

Lung Cancer Screening

Advances in imaging technology have ushered in a new era for lung cancer screening in high-risk individuals using computed tomographic (CT) scans. Although most published studies are nonrandomized observational cohorts of volunteers, the ability of CT scans to detect early stage lung cancer is undisputable. What is unresolved is the ability of spiral CT screening to affect lung cancer-related mortality. A large randomized trial sponsored by the National Cancer Institute to address this question is currently under way. Genomic and proteomic approaches promise to complement the ability of spiral CT to detect early lung cancer in the next few years. Currently, the decision to screen for lung cancer should involve a careful discussion with the individuals involved about the potential advantages, costs, and drawbacks of the approach.