Innovative molecular and imaging approaches for the detection of lung cancer and its precursor lesions

Enzyme-Driven Switchable Fluorescence-SERS Diagnostic Nanococktail for the Multiplex Detection of Lung Cancer Biomarkers

Comprehensive profiling of multiple protein targets plays a critical role in deeper understanding of specific disease conditions associated with high heterogeneity and complexity. Herein, we present the design and fabrication of smart programmable nanoarchitectures, which could integrate clinically relevant diagnostic modalities for the multiplexed detection of most prevalent panel of disease biomarkers present in lung cancer. The multiplex nanoprobes were prepared by attaching dual-functional Raman-active fluorogens onto spherical gold nanoparticles through a peptide linker, Phe-Lys-Cys (FKC), which is engineered with a cathepsin B (cathB) enzyme cleavage site. The presence of cathB induces the scission of FKC upon homing into the cancer cells, resulting in the release of the initially latent fluorophores with a concomitant quenching of the surface-enhanced Raman signal intensity, thereby realizing an on-off switching between the fluorescence and Raman modalities. The enzyme-triggered switchable nanoprobes were utilized for the simultaneous detection of pathologically relevant lung cancer targets by tethering with specific antibody units. The multiplex-targeted multicolor coded detection capability of the antitags was successfully developed as a valid protein screening methodology, which can address the unmet challenges in the conventional clinical scenario for the precise and early diagnosis of lung cancer.

Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer

Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.

Raman and autofluorescence spectrum dynamics along the HRG-induced differentiation pathway of MCF-7 cells

Cellular differentiation proceeds along complicated pathways, even when it is induced by extracellular signaling molecules. One of the major reasons for this complexity is the highly multidimensional internal dynamics of cells, which sometimes causes apparently stochastic responses in individual cells to extracellular stimuli. Therefore, to understand cell differentiation, it is necessary to monitor the internal dynamics of cells at single-cell resolution. Here, we used a Raman and autofluorescence spectrum analysis of single cells to detect dynamic changes in intracellular molecular components. MCF-7 cells are a human cancer-derived cell line that can be induced to differentiate into mammary-gland-like cells with the addition of heregulin (HRG) to the culture medium. We measured the spectra in the cytoplasm of MCF-7 cells during 12 days of HRG stimulation. The Raman scattering spectrum, which was the major component of the signal, changed with time. A multicomponent analysis of the Raman spectrum revealed that the dynamics of the major components of the intracellular molecules, including proteins and lipids, changed cyclically along the differentiation pathway. The background autofluorescence signals of Raman scattering also provided information about the differentiation process. Using the total information from the Raman and autofluorescence spectra, we were able to visualize the pathway of cell differentiation in the multicomponent phase space.

Multiplex detection of lung cancer cells at the single-molecule level

We develop a simple and sensitive method for multiplex detection of lung cancer cells at the single-molecule level, with a detection limit of 15 cells per mL for A549 cells and 4 cells per mL for H23 cells, without the involvement of any sequence-based amplification. This method holds great potential for further application in early clinical diagnosis, especially for the detection of rare tumor cells.

Widefield optical imaging of changes in uptake of glucose and tissue extracellular pH in head and neck cancer

The overall objective of this study was to develop an optical imaging approach to simultaneously measure altered cell metabolism and changes in tissue extracellular pH with the progression of cancer using clinically isolated biopsies. In this study, 19 pairs of clinically normal and abnormal biopsies were obtained from consenting patients with head and neck cancer at University of California, Davis Medical Center. Fluorescence intensity of tissue biopsies before and after topical delivery of 2-NBDG (2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy-D-glucose) and Alexa 647-pHLIP [pH (low) insertion peptide] was measured noninvasively by widefield imaging, and correlated with pathologic diagnosis. The results of widefield imaging of clinical biopsies demonstrated that 2-NBDG and pHLIP peptide can accurately distinguish the pathologically normal and abnormal biopsies. The results also demonstrated the potential of this approach to detect subepithelial lesions. Topical application of the contrast agents generated a significant increase in fluorescence contrast (3- to 4-fold) in the cancer biopsies as compared with the normal biopsies, irrespective of the patient and location of the biopsy within a head and neck cavity. This unpaired comparison across all the patients with cancer in this study highlights the specificity of the imaging approach. Furthermore, the results of this study indicated that changes in intracellular glucose metabolism and cancer acidosis are initiated in the early stages of cancer, and these changes are correlated with the progression of the disease. In conclusion, this novel optical molecular imaging approach to measure multiple biomarkers in cancer has a significant potential to be a useful tool for improving early detection and prognostic evaluation of oral neoplasia.

Advances and future directions in interventional pulmonology

The term "interventional pulmonology" (IP) supersedes the previously used term "thoracic endoscopy," a change that reflects the evolution of a specialty devoted to performing highly sophisticated and technologically advanced procedures in the lungs and chest. Continuing advances in technology promise to further expand IP's diagnostic and therapeutic frontiers. However, standardized educational programs to train and test IP physicians will be essential to maintain a high standard of practice in the field.

Lung cancer staging: clinical and radiologic perspectives

Published in 2009, the 7th edition of the American Joint Committee on Cancer TNM staging system is the culmination of an extensive worldwide initiative to standardize and validate lung cancer staging. Unlike prior editions, the new staging system is now inclusive of small cell carcinoma and carcinoid tumors. In addition, significant changes were made to the T and M descriptors, resulting in improved prognostic stratification of disease. This review article highlights these changes, the rationale for their inclusion in the new staging manual, and the role of the radiologist in determining stage.

Differential diagnosis of lung carcinoma with coherent anti-Stokes Raman scattering imaging

Aimed at bridging imaging technology development with cancer diagnosis, this paper first presents the prevailing challenges of lung cancer detection and diagnosis, with an emphasis on imaging techniques. It then elaborates on the working principle of coherent anti-Stokes Raman scattering microscopy, along with a description of pathologic applications to show the effectiveness and potential of this novel technology for lung cancer diagnosis. As a nonlinear optical technique probing intrinsic molecular vibrations, coherent anti-Stokes Raman scattering microscopy offers an unparalleled, label-free strategy for clinical cancer diagnosis and allows differential diagnosis of fresh specimens based on cell morphology information and patterns, without any histology staining. This powerful feature promises a higher biopsy yield for early cancer detection by incorporating a real-time imaging feed with a biopsy needle. In addition, molecularly targeted therapies would also benefit from early access to surgical specimen with high accuracy but minimum tissue consumption, therefore potentially saving specimens for follow-up diagnostic tests. Finally, we also introduce the potential of a coherent anti-Stokes Raman scattering-based endoscopy system to support intraoperative applications at the cellular level.

A minimally invasive multimodality image-guided (MIMIG) system for peripheral lung cancer intervention and diagnosis

BACKGROUND

Lung cancer is the leading cause of cancer-related death in the United States, with more than half of the cancers are located peripherally. Computed tomography (CT) has been utilized in the last decade to detect early peripheral lung cancer. However, due to the high false diagnosis rate of CT, further biopsy is often necessary to confirm cancerous cases. This renders intervention for peripheral lung nodules (especially for small peripheral lung cancer) difficult and time-consuming, and it is highly desirable to develop new, on-the-spot earlier lung cancer diagnosis and treatment strategies.

PURPOSE

The objective of this study is to develop a minimally invasive multimodality image-guided (MIMIG) intervention system to detect lesions, confirm small peripheral lung cancer, and potentially guide on-the-spot treatment at an early stage. Accurate image guidance and real-time optical imaging of nodules are thus the key techniques to be explored in this work.

METHODS

The MIMIG system uses CT images and electromagnetic (EM) tracking to help interventional radiologists target the lesion efficiently. After targeting the lesion, a fiber-optic probe coupled with optical molecular imaging contrast agents is used to confirm the existence of cancerous tissues on-site at microscopic resolution. Using the software developed, pulmonary vessels, airways, and nodules can be segmented and visualized for surgical planning; the segmented results are then transformed onto the intra-procedural CT for interventional guidance using EM tracking. Endomicroscopy through a fiber-optic probe is then performed to visualize tumor tissues. Experiments using IntegriSense 680 fluorescent contrast agent labeling αvβ3 integrin were carried out for rabbit lung cancer models. Confirmed cancers could then be treated on-the-spot using radio-frequency ablation (RFA).

RESULTS

The prototype system is evaluated using the rabbit VX2 lung cancer model to evaluate the targeting accuracy, guidance efficiency, and performance of molecular imaging. Using this system, we achieved an average targeting accuracy of 3.04 mm, and the IntegriSense signals within the VX2 tumors were found to be at least two-fold higher than those of normal tissues. The results demonstrate great potential for applying the system in human trials in the future if an optical molecular imaging agent is approved by the Food and Drug Administration (FDA).

CONCLUSIONS

The MIMIG system was developed for on-the-spot interventional diagnosis of peripheral lung tumors by combining image-guidance and molecular imaging. The system can be potentially applied to human trials on diagnosing and treating earlier stage lung cancer. For current clinical applications, where a biopsy is unavoidable, the MIMIG system without contrast agents could be used for biopsy guidance to improve the accuracy and efficiency.

On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification

We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

Clinical validation of an autoantibody test for lung cancer

Background: Autoantibodies may be present in a variety of underlying cancers several years before tumours can be detected and testing for their presence may allow earlier diagnosis. We report the clinical validation of an autoantibody panel in newly diagnosed patients with lung cancer (LC).

Patients and methods: Three cohorts of patients with newly diagnosed LC were identified: group 1 (n = 145), group 2 (n = 241) and group 3 (n = 269). Patients were individually matched by gender, age and smoking history to a control individual with no history of malignant disease. Serum samples were obtained after diagnosis but before any anticancer treatment. Autoantibody levels were measured against a panel of six tumour-related antigens (p53, NY-ESO-1, CAGE, GBU4-5, Annexin 1 and SOX2). Assay sensitivity was tested in relation to demographic variables and cancer type/stage.

Results: The autoantibody panel demonstrated a sensitivity/specificity of 36%/91%, 39%/89% and 37%/90% in groups 1, 2 and 3, respectively, with good reproducibility. There was no significant difference between different LC stages, indicating that the antigens included covered the different types of LC well.

Conclusion: This assay confirms the value of an autoantibody panel as a diagnostic tool and offers a potential system for monitoring patients at high risk of LC.

Emerging roles for multimodal optical imaging in early cancer detection: a global challenge

Medical imaging technologies have become increasingly important in the clinical management of cancer, and now play key roles in cancer screening, diagnosis, staging, and monitoring response to treatment. Standard imaging modalities such as MRI, PET, and CT require significant financial resources and infrastructure, which limits access to these modalities to those patients in high-resource settings. In contrast, optical imaging strategies, with the potential for reduced cost and enhanced portability, are emerging as additional tools to facilitate the early detection and diagnosis of cancer. This article presents a vision for an expanding role for optical imaging in global cancer management, including screening, early detection at the point-of-care, biopsy guidance, and real-time histology. Multi-modal optical imaging - the combination of widefield and high resolution imaging - has the potential to aid in the detection and management of precancer and early cancer for traditionally underserved populations. Several recent widefield and high-resolution optical imaging technologies are described, along with requirements for implementing such devices into lower-resource - settings.

Patient-derived first generation xenografts of non-small cell lung cancers: promising tools for predicting drug responses for personalized chemotherapy

PURPOSE

Current chemotherapeutic regimens have only modest benefit for non-small cell lung cancer (NSCLC) patients. Cumulative toxicities/drug resistance limit chemotherapy given after the first-line regimen. For personalized chemotherapy, clinically relevant NSCLC models are needed for quickly predicting the most effective regimens for therapy with curative intent. In this study, first generation subrenal capsule xenografts of primary NSCLCs were examined for (a) determining responses to conventional chemotherapeutic regimens and (b) selecting regimens most effective for individual patients.

EXPERIMENTAL DESIGN

Pieces (1x3x3 mm(3)) of 32 nontreated, completely resected patients' NSCLCs were grafted under renal capsules of nonobese diabetic/severe combined immunodeficient mice and treated with (A) cisplatin+vinorelbine, (B) cisplatin+docetaxel, (C) cisplatin+gemcitabine, and positive responses (treated tumor area <or=50% of control, P < 0.05) were determined. Clinical outcomes of treated patients were acquired.

RESULTS

Xenografts from all NSCLCs were established (engraftment rate, 90%) with the retention of major biological characteristics of the original cancers. The entire process of drug assessment took 8 weeks. Response rates to regimens A, B, and C were 28% (9 of 32), 42% (8 of 19), and 44% (7 of 16), respectively. Certain cancers that were resistant to a particular regimen were sensitive to others. The majority of responsive tumors contained foci of nonresponding cancer cells, indicative of tumor heterogeneity and potential drug resistance. Xenografts from six of seven patients who developed recurrence/metastasis were nonresponsive.

CONCLUSIONS

Models based on first generation NSCLC subrenal capsule xenografts have been developed, which are suitable for quick assessment (6-8 weeks) of the chemosensitivity of patients' cancers and selection of the most effective regimens. They hold promise for application in personalized chemotherapy of NSCLC patients.

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.

[Early diagnosis of lung cancer: impact of autofluorescence bronchoscopy]

INTRODUCTION

Less than 15% of all patients survive five years after a diagnosis of lung cancer. This poor prognosis is attributed to a lack of early detection. Among the methods of early diagnosis of bronchial cancer, autofluorescence bronchoscopy allows for the early identification of preinvasive bronchial lesions. The goal of this prospective study is to evaluate the contribution of the autofluorescence bronchoscopy, on a hospital site, over a period of one year.

METHODS

All patients with an indication of autofluorescence bronchoscopy were included in the study. The following parameters were collected: age, sex, smoking status, FEV1, FVC, biopsy sites, histology, duration of examination.

RESULTS

Two hundred and seventy-four patients were included. The average age was 63.8 years (+/-12), the smoking status was 35 packs/year (+/-19). A fluorescence abnormality was detected in 131 patients and 165 sites were biopsied. An histological abnormality was found in 76% of the samples, with 34 hyperplasia (28%), 56 squamous metaplasia (46%), three mild dysplasia (3%), two moderate dysplasia (2%), one severe dysplasia (1%), two carcinomas in situ (2%) and 21 invasive carcinomas (18%).

CONCLUSION

Autofluorescence bronchoscopy is an effective examination for the detection of the preinvasive neoplasic lesions and may be proposed when lung cancer is suspected.

Connective tissue-activating peptide III: a novel blood biomarker for early lung cancer detection

PURPOSE

There are no reliable blood biomarkers to detect early lung cancer. We used a novel strategy that allows discovery of differentially present proteins against a complex and variable background.

METHODS

Mass spectrometry analyses of paired pulmonary venous-radial arterial blood from 16 lung cancer patients were applied to identify plasma proteins potentially derived from the tumor microenvironment. Two differentially expressed proteins were confirmed in 64 paired venous-arterial blood samples using an immunoassay. Twenty-eight pre- and postsurgical resection peripheral blood samples and two independent, blinded sets of plasma from 149 participants in a lung cancer screening study (49 lung cancers and 100 controls) and 266 participants from the National Heart Lung and Blood Institute Lung Health Study (45 lung cancer and 221 matched controls) determined the accuracy of the two protein markers to detect subclinical lung cancer.

RESULTS

Connective tissue-activating peptide III (CTAP III)/ neutrophil activating protein-2 (NAP-2) and haptoglobin were identified to be significantly higher in venous than in arterial blood. CTAP III/NAP-2 levels decreased after tumor resection (P = .01). In two independent population cohorts, CTAP III/NAP-2 was significantly associated with lung cancer and improved the accuracy of a lung cancer risk prediction model that included age, smoking, lung function (FEV(1)), and an interaction term between FEV(1) and CTAP III/NAP-2 (area under the curve, 0.84; 95% CI, 0.77 to 0.91) compared to CAPIII/NAP-2 alone.

CONCLUSION

We identified CTAP III/NAP-2 as a novel biomarker to detect preclinical lung cancer. The study underscores the importance of applying blood biomarkers as part of a multimodal lung cancer risk prediction model instead of as stand-alone tests.

DNA methylation-based biomarkers for early detection of non-small cell lung cancer: an update

Lung cancer is the number one cancer killer in the United States. This disease is clinically divided into two sub-types, small cell lung cancer, (10–15% of lung cancer cases), and non-small cell lung cancer (NSCLC; 85–90% of cases). Early detection of NSCLC, which is the more common and less aggressive of the two sub-types, has the highest potential for saving lives. As yet, no routine screening method that enables early detection exists, and this is a key factor in the high mortality rate of this disease. Imaging and cytology-based screening strategies have been employed for early detection, and while some are sensitive, none have been demonstrated to reduce lung cancer mortality. However, mortality might be reduced by developing specific molecular markers that can complement imaging techniques. DNA methylation has emerged as a highly promising biomarker and is being actively studied in multiple cancers. The analysis of DNA methylation-based biomarkers is rapidly advancing, and a large number of potential biomarkers have been identified. Here we present a detailed review of the literature, focusing on DNA methylation-based markers developed using primary NSCLC tissue. Viable markers for clinical diagnosis must be detectable in 'remote media' such as blood, sputum, bronchoalveolar lavage, or even exhaled breath condensate. We discuss progress on their detection in such media and the sensitivity and specificity of the molecular marker panels identified to date. Lastly, we look to future advancements that will be made possible with the interrogation of the epigenome.

New imaging approaches for understanding lung cancer response to treatment

The survival rate for lung cancer patients has barely improved over the past 30 years. New evaluation benchmarks for cancer response are needed to test therapy agents in a cost-effective and timely manner. From recent work, it is evident that primary lung cancers are very complex structures containing not only cancerous cells but also fibrotic and inflammatory cells and necrotic tissue. A greater understanding of the three-dimensional structure of primary lung cancer is emerging, allowing for the first time an appreciation of how this biomass is represented in medical imaging data. It is only through a greater understanding of the lung cancer biomass that we can define rational and early-response measures, including specific cellular responses such as cancer cell death or growth inhibition. In doing so, we can define response metrics that will shorten new drug discovery times and reduce costs, allowing for the evaluation of many more agents with therapeutic potential.

Molecular recognition of small-cell lung cancer cells using aptamers

Early diagnosis is the way to improve the rate of lung cancer survival, but is almost impossible today due to the lack of molecular probes that recognize lung cancer cells sensitively and selectively. We developed a new aptamer approach for the recognition of specific small-cell lung cancer (SCLC) cell-surface molecular markers. Our approach relies on cell-based systematic evolution of ligands by exponential enrichment (cell-SELEX) to evolve aptamers for whole live cells that express a variety of surface markers representing molecular differences among cancer cells. When applied to different lung cancer cells including those from patient samples, these aptamers bind to SCLC cells with high affinity and specificity in various assay formats. When conjugated with magnetic and fluorescent nanoparticles, the aptamer nanoconjugates could effectively extract SCLC cells from mixed cell media for isolation, enrichment, and sensitive detection. These studies demonstrate the potential of the aptamer approach for early lung cancer detection.

Aberrant promoter hypermethylation in serum DNA from patients with silicosis

It is well established that patients with silicosis are at high risk for lung cancer; however, it is difficult to detect lung cancer by chest radiography during follow-up treatment of patients with silicosis because of preexisting diffuse pulmonary shadows. The purpose of this study is to evaluate the usefulness of detection of serum DNA methylation for early detection of lung cancer in silicosis. Serum samples from healthy controls (n = 20) and silicosis patients with (n = 11) and without (n = 67) lung cancer were tested for aberrant hypermethylation at the promoters of the DNA repair gene O(6)-methylguanine-DNA methyltransferase (MGMT), p16(INK4a), ras association domain family 1A (RASSF1A), the apoptosis-related gene death-associated protein kinase (DAPK) and retinoic acid receptor beta (RARbeta) by methylation-specific polymerase chain reaction. Aberrant promoter methylation in at least one of five tumor suppressor genes was detected more frequently in the serum DNA of silicosis patients with lung cancer than in that of patients without it (P = 0.006). Furthermore, the odds ratio of having lung cancer was 9.77 (P = 0.009) for those silicosis patients with methylation of at least one gene. Extended exposure to silica (>30 years) was correlated with an increased methylation frequency (P = 0.017); however, methylation status did not correlate with age, smoking history or radiographic findings of silicosis. These results suggest that testing for aberrant promoter methylation of tumor suppressor genes using serum DNA may facilitate early detection of lung cancer in patients with silicosis.

Identification of a panel of sensitive and specific DNA methylation markers for squamous cell lung cancer

Background

Lung cancer is the leading cause of cancer death in men and women in the United States and Western Europe. Over 160,000 Americans die of this disease every year. The five-year survival rate is 15% – significantly lower than that of other major cancers. Early detection is a key factor in increasing lung cancer patient survival. DNA hypermethylation is recognized as an important mechanism for tumor suppressor gene inactivation in cancer and could yield powerful biomarkers for early detection of lung cancer. Here we focused on developing DNA methylation markers for squamous cell carcinoma of the lung. Using the sensitive, high-throughput DNA methylation analysis technique MethyLight, we examined the methylation profile of 42 loci in a collection of 45 squamous cell lung cancer samples and adjacent non-tumor lung tissues from the same patients.

Results

We identified 22 loci showing significantly higher DNA methylation levels in tumor tissue than adjacent non-tumor lung. Of these, eight showed highly significant hypermethylation in tumor tissue (p < 0.0001): GDNF, MTHFR, OPCML, TNFRSF25, TCF21, PAX8, PTPRN2 and PITX2. Used in combination on our specimen collection, this eight-locus panel showed 95.6% sensitivity and specificity.

Conclusion

We have identified 22 DNA methylation markers for squamous cell lung cancer, several of which have not previously been reported to be methylated in any type of human cancer. The top eight markers show great promise as a sensitive and specific DNA methylation marker panel for squamous cell lung cancer.

Endogenous optical biomarkers of ovarian cancer evaluated with multiphoton microscopy

PURPOSE

Among gynecologic cancers, ovarian cancer is the second most common and has the highest mortality. Currently, there is no accurate early diagnostic technique for ovarian cancer. Furthermore, little is understood regarding the early progression of this disease. We have imaged multiphoton interactions of endogenous tissue constituents from normal and abnormal ovarian biopsies that were kept viable during transport from the operating room and microscopy.

EXPERIMENTAL DESIGN

The ovarian surface and underlying stroma were assessed with two-photon excited fluorescence (2PEF) and second harmonic generation (SHG). High-resolution, optically sectioned images were analyzed for epithelial morphology based on 2PEF and collagen density and structural integrity based on SHG. Additionally, multiwavelength 2PEF provided an estimation of the cellular redox ratio of epithelial cells.

RESULTS

Normal tissue exhibited a uniform epithelial layer with highly structured collagen in the stroma, whereas abnormal tissue exhibited varied epithelium with large cells and substantial quantitative changes to the collagen structure. Samples from patients at high risk for developing ovarian cancer (based on their personal/family history of cancer) exhibited highly variable cellular redox ratios and changes in collagen structure that trended toward cancer samples.

CONCLUSION

This study highlights differences in endogenous signals in viable ovarian biopsies based on quantitative collagen structural changes and redox ratio estimates that may lead to improved detection and further insights in ovarian cancer, particularly in the early stages of the disease.

Early detection and chemoprevention of lung cancer

Lung cancer is the most common cause of cancer death worldwide with more than 1.3 million people dying of the disease annually. While antitobacco initiatives in young people are important in preventing lung cancer in the long term, additional measures such as early detection and chemoprevention are needed for individuals already at risk due to past exposure to tobacco smoke. This review highlights the potential use of sputum, exhaled breath and blood biomarkers as well as thoracic CT and autofluorescence bronchoscopy for early detection. The current status of chemoprevention is summarized. The case for using a two-step screening strategy is also discussed.

Chemoprevention in lung carcinogenesis--an overview

Lung cancer ranks among the most commonly occurring malignancies and is currently the leading cause of cancer-related death worldwide. This is due to its late diagnosis and relative resistance to standard oncological treatment approaches. The heavy burden of lung cancer and its treatment resistance have elicited an intense interest in the promising approach of chemoprevention. Chemoprevention is defined as a pharmacologic intervention to suppress or reverse the carcinogenic process and the lung is one of the most studied sites for cancer chemoprevention. This review, with a short update on pulmonary carcinogenesis, will summarize the available knowledge of chemoprevention trials and agents with a preventive potential in the 'lung field'.

Lung cancer screening

PURPOSE OF REVIEW

Advances in imaging technologies and biomarker research offer hope that the incidence and mortality of lung cancer can be reduced by screening similar to what have been achieved for cancer of the cervix, breast, and colon.

RECENT FINDINGS

Spiral computed tomography with multitrack scanners and autofluorescence bronchoscopy offer unprecedented sensitivity to detect lung cancer even during the preinvasive stage. The high sensitivity of these tests, however, is associated with a low specificity. Better selection of individuals at highest risk of lung cancer using biomarkers in sputum, blood, or exhaled breath, as well as a better understanding of genetic susceptibility, may improve their positive predictive values, minimize unnecessary downstream investigations or treatment, as well as reduce screening costs.

SUMMARY

Improvement in the performance of sputum, exhaled breath, or blood biomarkers holds promise as the first screening step to identify individuals at highest risk of lung cancer beyond what age and smoking could predict to select those who would obtain the most benefits from spiral computed tomography or autofluorescence bronchoscopy as localization tools.

An image model and segmentation algorithm for reflectance confocal images of in vivo cervical tissue

The automatic segmentation of nuclei in confocal reflectance images of cervical tissue is an important goal toward developing less expensive cervical precancer detection methods. Since in vivo confocal reflectance microscopy is an emerging technology for cancer detection, no prior work has been reported on the automatic segmentation of in vivo confocal reflectance images. However, prior work has shown that nuclear size and nuclear-to-cytoplasmic ratio can determine the presence or extent of cervical precancer. Thus, segmenting nuclei in confocal images will aid in cervical precancer detection. Successful segmentation of images of any type can be significantly enhanced by the introduction of accurate image models. To enable a deeper understanding of confocal reflectance microscopy images of cervical tissue, and to supply a basis for parameter selection in a classification algorithm, we have developed a model that accounts for the properties of the imaging system and of the tissues. Using our model in conjunction with a powerful image enhancement tool (anisotropic median-diffusion), appropriate statistical image modeling of spatial interactions (Gaussian Markov random fields), and a Bayesian framework for classification-segmentation, we have developed an effective algorithm for automatically segmenting nuclei in confocal images of cervical tissue. We have applied our algorithm to an extensive set of cervical images and have found that it detects 90% of hand-segmented nuclei with an average of 6 false positives per frame.

Chromosome 5p aberrations are early events in lung cancer: implication of glial cell line-derived neurotrophic factor in disease progression

Lung cancer is the most widely diagnosed malignancy in the world. Understanding early-stage disease will give insight into its pathogenesis. Despite the fact that pre-invasive lesions are challenging to isolate, and often yield insufficient DNA for the analysis of multiple loci, genomic profiling of such lesions will lead to the discovery of causal genetic alterations, which may be otherwise masked by the gross instability associated with tumors. In this study, we report the identification of multiple early genetic events on chromosome 5p in lung cancer progression. Using a high-resolution 5p-specific genomic array, which contains a tiling path of DNA segments for comparative genomic hybridization, nine novel minimal regions of loss and gain were discovered in bronchial carcinoma in situ (CIS) specimens. Within these regions we identified two candidate genes novel to lung cancer. The 0.27 Mbp region at 5p15.2 contains a single gene, Triple Functional Domain, which we determined to be differentially expressed in tumors. The 0.34 Mbp region at 5p13.2 contains Glial Cell Line-Derived Neurotrophic Factor (GDNF), which is a ligand for the RET oncogene product and is normally expressed during lung development (but absent in adult lung tissue). Our data showed not only that GDNF is overexpressed at the transcript level in squamous non-small-cell lung carcinoma, but also that the GDNF protein is present in early-stage lesions. Reactivation of the fetal lung expressed GDNF in early lesions and its amplification in CIS suggests an early role in tumorigenesis. These results highlight the value of examining the genomes of pre-invasive stages of cancer at tiling resolution.

Identification of Epigenetic Aberrant Promoter Methylation in Serum DNA Is Useful for Early Detection of Lung Cancer

Purpose: The purpose of this study is to evaluate the usefulness of serum DNA methylation of five tumor suppressor genes for early detection of lung cancer.

Experimental Design: Methylation status in serum DNA from 200 patients undergoing bronchofiberscopic examination for abnormal findings on chest radiograph detected by lung cancer screening or surveillance was examined using methylation-specific PCR.

Results: Ninety-one patients were given a pathologic diagnosis of lung cancer, 9 other malignant diseases, and 100 nonmalignant pulmonary diseases. In patients with lung cancer, methylation was detected in 18.7% for MGMT, 15.4% for p16INK4a, 12.1% for RASSF1A, 11.0% for DAPK, and 6.6% for RAR-β, which was higher compared with that in patients with nonmalignant diseases. Age and smoking status seemed to associate with methylation status. Sensitivity, specificity, and predictive value of methylation in at least one gene for diagnosis of lung cancer were 49.5%, 85.0%, and 75.0%, respectively. Adjusted odds ratio (95% confidence interval) for having lung cancer was 5.28 (2.39-11.7) for patients with methylation in one gene and 5.89 (1.53-22.7) for those with methylation in two or more genes. It is of note that methylation was identified in 50.9% of stage I lung cancer patients, whereas serum protein tumor markers were positive in 11.3% of them.

Conclusions: These results suggest that identification of promoter methylation of tumor suppressor genes in serum DNA could be useful for early detection of lung cancer.

Involvement of multiple developmental genes on chromosome 1p in lung tumorigenesis

Lung cancer is the leading cause of cancer death in North America. Despite advances in lung cancer treatment, the overall 5 year survival rate for those diagnosed with the disease is bleak presumably due to the late stage of diagnosis. Owing to the difficulty of early detection, preneoplastic specimens are rare. However, studying both preinvasive and invasive stages of disease is necessary to fully understand lung cancer progression. Aberration of chromosome arm 1p is common in lung and other cancers. In this study, we used a genomic array with complete tiling coverage of 1p to profile preinvasive and invasive squamous non-small cell lung carcinoma samples. With this technology, multiple novel submegabase alterations were identified. Three of the 1p alterations harbored genes belonging to gene families known to be involved in cancer development through either the Wnt or the Notch developmental pathways. Our finding of a 0.4 Mb amplified region at 1p36.12 containing WNT4 in preinvasive lung cancer, coupled with the identification of three additional alterations in invasive tumors that also contain genes related to the Notch and Wnt pathways, strongly suggests an intricate role of these pathways in early and late stages of lung cancer development. Furthermore, ectopic expression of DVL1, LRP8 and Notch2 in malignant lung tissue validates the biological impact of these genetic alterations. Importantly, this implication of pathways known only to be activated in fetal lung development lends support to the proposed model of lung cancer ontology whereby tumors arise from dysregulated pleuripotent stem cells.

Virtual bronchoscopy for evaluation of airway disease

The data presented above indicate that VB is a novel and extremely useful modality for airway evaluation in patients who have benign and malignant disease. VB is noninvasive, with no additional radiation exposure relative to standard CT scans of the chest. Commercial software allows for the interactivity of 2D and 3D images. The ability to examine 2D and 3D anatomic detail from multiple directions enables precise assessment of intraluminal and extraluminal pathology. The authors' experience indicates that VB is a superb modality for assessing the length of airway stenoses and ascertaining airway patency distal to these lesions (Fig. 6). As such, VB has proven to be extremely useful for determining the feasibility of endobronchial procedures such as dilations, stent placements, and laser ablation of endobronchial tumors. Ferretti et al [27] observed that VB is an excellent noninvasive means for long-term monitoring of tracheobronchial stents. Furthermore, the authors have found VB useful for guiding the bronchoscopic evaluation of patients who have intermittent hemoptysis secondary to lesions in peripheral airways. The 3D anatomic detail provided by VB has proven useful for assessing the feasibility of lung-sparing procedures in patients who have limited pulmonary reserve and for sequentially evaluating treatment response in patients who have inoperable disease. Currently, the main limitation of VB pertains to its inability to evaluate the mucosal surface of the respiratory tract reliably. Although form can be detected, mucosal color, irregularity, or friability cannot be assessed. As such, VB cannot be used for routine surveillance of patients at high risk of developing airway malignancies. The development of novel aerosolized contrast agents or spectroscopic techniques that can discriminate benign versus malignant mucosal tissues might enhance the sensitivity and specificity of VB for the detection of preinvasive cancers within the respiratory tract.

Genetic alteration and gene expression modulation during cancer progression

Cancer progresses through a series of histopathological stages. Progression is thought to be driven by the accumulation of genetic alterations and consequently gene expression pattern changes. The identification of genes and pathways involved will not only enhance our understanding of the biology of this process, it will also provide new targets for early diagnosis and facilitate treatment design. Genomic approaches have proven to be effective in detecting chromosomal alterations and identifying genes disrupted in cancer. Gene expression profiling has led to the subclassification of tumors. In this article, we will describe the current technologies used in cancer gene discovery, the model systems used to validate the significance of the genes and pathways, and some of the genes and pathways implicated in the progression of preneoplastic and early stage cancer.

Comparative evaluation of super high-resolution CT scan and virtual bronchoscopy for the detection of tracheobronchial malignancies

OBJECTIVES

Novel imaging modalities are currently available for the noninvasive evaluation of the tracheobronchial tree. This study was undertaken to compare the diagnostic potentials of conventional CT scanning, super high-resolution CT (SHR-CT) scanning, and virtual bronchoscopy (VB) directly with fiberoptic bronchoscopy (FB) for the detection of tracheobronchial neoplasms.

DESIGN

Prospective observer study, in which 44 consecutive patients with thoracic malignancies were evaluated using several diagnostic imaging modalities. Images of the thorax were interpreted by individuals blind to the results of FB for the detection of endoluminal, obstructive, or mucosal lesions.

MEASUREMENTS AND RESULTS

Image acquisition and simulation of the tracheobronchial anatomy were created successfully in all patients. Thirty-two patients who underwent both SHR-CT scanning and VB had correlative FBs within 1 month. In all nine patients who had a normal anatomy, SHR-CT scanning and VB accurately correlated with the FB findings. However, CT scanning demonstrated two false-positive obstructive lesions in one patient. Twenty-three patients had a total of 35 abnormal FB findings. The sensitivities of SHR-CT scanning and VB for the detection of endoluminal, obstructive, and mucosal lesions were 90%, 100%, and 16%, respectively. The overall sensitivities and specificities of SHR-CT scanning and VB were 83% and 100%, respectively. In contrast, CT scanning had sensitivities of 50%, 72%, and 0% for the detection of endoluminal, obstructive, and mucosal lesions with an overall sensitivity and specificity of 59%, and 85%, respectively. There was no case in which conventional CT scanning was better at detecting lesions than either SHR-CT scanning or VB.

CONCLUSIONS

SHR-CT scanning and VB are accurate, noninvasive methods for identifying obstructions and endoluminal lesions within the respiratory tract. Thus, these novel imaging techniques are valuable as complementary modalities to FB, providing information that is useful for the detection and management of airway malignancies.

Lung cancer screening: a different paradigm

Thoracic computed tomography (CT) is a sensitive method for detecting early lung cancer but has a high false-positive rate and is not sensitive for detecting central preinvasive and microinvasive cancer. Our hypothesis was that automated quantitative image cytometry (AQC) of sputum cells as the first screening method may improve detection rate by identifying individuals at highest risk for lung cancer. A total of 561 volunteer current or former smokers 50 years of age or older, with a smoking history of more than or equal to 30 pack/years, were studied. Among these, 423 were found to have sputum atypia defined as five cells or more with abnormal DNA content using AQC. Noncalcified pulmonary nodules were found in 46% (259/561). Of the 14 detected cancers, 13 were detected in subjects with sputum atypia-nine by CT and four carcinoma in situ/microinvasive cancers by autofluorescence bronchoscopy. One cancer was detected by CT alone. AQC of sputum cells improved the detection rate of lung cancer from 1.8 to 3.1%. CT scan alone would have missed 29% of the cancers. This screening paradigm shift has the additional potential of reducing the number of initial CT scans by at least 25% with further savings in follow-up investigations and treatment.

Virtual bronchoscopy: comparison of different surface rendering models

The aim of this study was to compare different representation models of surface-rendered virtual bronchoscopy. 10 consecutive patients with inoperable primary lung tumors underwent thin-section spiral computed tomography. The structures of interest, the tracheobronchial system and anatomical and pathological thoracic structures were segmented using an interactive threshold interval volume-growing segmentation algorithm and visualized with the aid of a color-coded surface rendering method. For virtual bronchoscopy, the tracheobronchial system was visualized using a triangle-surface rendering model, a shaded-surface rendering model and a transparent shaded-surface rendering model. The triangle-surface rendering model allowed optimum detailed spatial representation of the dimensions of extraluminal anatomical and pathological mediastinal structures. As the lumen of the tracheobronchial system was less well defined, the rendering model was of limited use for depiction of the airway surface. The shaded-surface rendering model facilitated an optimum assessment of the airway surface, but the mediastinal structures could not be depicted. The transparent shaded-surface rendering model provides simultaneous adequate to optimum visualization and assessment of the intraluminal airway surface and the extraluminal mediastinal structures as well as a quantitative assessment of the spatial relationship between these structures. Fast data acquisition with a multi-slice detector spiral computed tomography scanner and the use of virtual bronchoscopy with the transparent shaded-surface rendering model obviate the need for time consuming detailed analysis and presentation of axial source images by providing improved the diagnostic imaging of endotracheal and endobronchial diseases and offering a useful alternative to fiberoptic bronchoscopy.