Application of proteomics to cancer early detection

Structure-changeable luminescent Eu(III) complex as a human cancer grade probing system for brain tumor diagnosis

Accurate determination of human tumor malignancy is important for choosing efficient and safe therapies. Bioimaging technologies based on luminescent molecules are widely used to localize and distinguish active tumor cells. Here, we report a human cancer grade probing system (GPS) using a water-soluble and structure-changeable Eu(III) complex for the continuous detection of early human brain tumors of different malignancy grades. Time-dependent emission spectra of the Eu(III) complexes in various types of tumor cells were recorded. The radiative rate constants (kr), which depend on the geometry of the Eu(III) complex, were calculated from the emission spectra. The tendency of the kr values to vary depended on the tumor cells at different malignancy grades. Between T = 0 and T = 3 h of invasion, the kr values exhibited an increase of 4% in NHA/TS (benign grade II gliomas), 7% in NHA/TSR (malignant grade III gliomas), and 27% in NHA/TSRA (malignant grade IV gliomas). Tumor cells with high-grade malignancy exhibited a rapid upward trend in kr values. The cancer GPS employs Eu(III) emissions to provide a new diagnostic method for determining human brain tumor malignancy.

C1QA and COMP: plasma-based biomarkers for early diagnosis of pancreatic neuroendocrine tumors

Pancreatic Neuroendocrine tumors (PanNET) are challenging to diagnose and often detected at advanced stages due to a lack of specific and sensitive biomarkers. This study utilized proteomics as a valuable approach for cancer biomarker discovery; therefore, mass spectrometry-based proteomic profiling was conducted on plasma samples from 12 subjects (3 controls; 5 Grade I, 4 Grade II PanNET patients) to identify potential proteins capable of effectively distinguishing PanNET from healthy controls. Data are available via ProteomeXchange with the identifier PXD045045. 13.2% of proteins were uniquely identified in PanNET, while 60% were commonly expressed in PanNET and controls. 17 proteins exhibiting significant differential expression between PanNET and controls were identified with downstream analysis. Further, 5 proteins (C1QA, COMP, HSP90B1, ITGA2B, and FN1) were selected by pathway analysis and were validated using Western blot analysis. Significant downregulation of C1QA (p = 0.001: within groups, 0.03: control vs. grade I, 0.0013: grade I vs. grade II) and COMP (p = 0.011: within groups, 0.019: control vs grade I) were observed in PanNET Grade I & II than in controls. Subsequently, ELISA on 38 samples revealed significant downregulation of C1QA and COMP with increasing disease severity. This study shows the potential of C1QA and COMP in the early detection of PanNET, highlighting their role in the search for early-stage (Grade-I and Grade-II) diagnostic markers and therapeutic targets for PanNET.

Proteomics: Its Promise and Pitfalls in Shaping Precision Medicine in Solid Organ Transplantation

Solid organ transplantation is an established treatment of choice for end-stage organ failure. However, all transplant patients are at risk of developing complications, including allograft rejection and death. Histological analysis of graft biopsy is still the gold standard for evaluation of allograft injury, but it is an invasive procedure and prone to sampling errors. The past decade has seen an increased number of efforts to develop minimally invasive procedures for monitoring allograft injury. Despite the recent progress, limitations such as the complexity of proteomics-based technology, the lack of standardization, and the heterogeneity of populations that have been included in different studies have hindered proteomic tools from reaching clinical transplantation. This review focuses on the role of proteomics-based platforms in biomarker discovery and validation in solid organ transplantation. We also emphasize the value of biomarkers that provide potential mechanistic insights into the pathophysiology of allograft injury, dysfunction, or rejection. Additionally, we forecast that the growth of publicly available data sets, combined with computational methods that effectively integrate them, will facilitate a generation of more informed hypotheses for potential subsequent evaluation in preclinical and clinical studies. Finally, we illustrate the value of combining data sets through the integration of 2 independent data sets that pinpointed hub proteins in antibody-mediated rejection.

A Novel NanoMIP-SPR Sensor for the Point-of-Care Diagnosis of Breast Cancer

Simple, fast, selective, and reliable detection of human epidermal growth factor receptor 2 (HER2) is of utmost importance in the early diagnosis of breast cancer to prevent its high prevalence and mortality. Molecularly imprinted polymers (MIPs), also known as artificial antibodies, have recently been used as a specific tool in cancer diagnosis and therapy. In this study, a miniaturized surface plasmon resonance (SPR)-based sensor was developed using epitope-mediated HER2-nanoMIPs. The nanoMIP receptors were characterized using dynamic light scattering (DLS), zeta potential, Fourier-transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), and fluorescent microscopy. The average size of the nanoMIPs was determined to be 67.5 ± 12.5 nm. The proposed novel SPR sensor provided superior selectivity to HER2 with a detection limit (LOD) of 11.6 pg mL^-1 in human serum. The high specificity of the sensor was confirmed by cross-reactivity studies using P53, human serum albumin (HSA), transferrin, and glucose. The sensor preparation steps were successfully characterized by employing cyclic and square wave voltammetry. The nanoMIP-SPR sensor demonstrates great potential for use in the early diagnosis of breast cancer as a robust tool with high sensitivity, selectivity, and specificity.

The Role of Proteomics and Phosphoproteomics in the Discovery of Therapeutic Targets and Biomarkers in Acquired EGFR-TKI-Resistant Non-Small Cell Lung Cancer

The discovery of potent EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has revolutionized the treatment of EGFR-mutated lung cancer. Despite the fact that EGFR-TKIs have yielded several significant benefits for lung cancer patients, the emergence of resistance to EGFR-TKIs has been a substantial impediment to improving treatment outcomes. Understanding the molecular mechanisms underlying resistance is crucial for the development of new treatments and biomarkers for disease progression. Together with the advancement in proteome and phosphoproteome analysis, a diverse set of key signaling pathways have been successfully identified that provide insight for the discovery of possible therapeutically targeted proteins. In this review, we highlight the proteome and phosphoproteomic analyses of non-small cell lung cancer (NSCLC) as well as the proteome analysis of biofluid specimens that associate with acquired resistance in response to different generations of EGFR-TKI. Furthermore, we present an overview of the targeted proteins and potential drugs that have been tested in clinical studies and discuss the challenges of implementing this discovery in future NSCLC treatment.

New thoughts and findings on invasion and metastasis of pancreatic ductal adenocarcinoma (PDAC) from comparative proteomics: multi-target therapy

As one of the most aggressive malignant tumors, pancreatic ductal adenocarcinoma (PDAC) ranks as the fourth cancer-related mortality in the world. The extremely low survival rate is closely related to early invasion and distant metastasis. However, effective target therapy for weakening its malignant behavior remains limited. Over the past decades, many proteins correlating with invasion and metastasis of PDAC have been discovered using proteomics. The discovery of these proteins gives us a deeper understanding of the invasive and migratory processes of PDAC. This review is a systemic integration of these proteomics findings over the past 10 years. The discovered proteins were typically associated with the glycolytic process, hypoxic microenvironment, post-translational modification, extracellular matrix, exosomes, cancer stem cells, and immune escape. Some proteins were found to have multiple functions, and, cooperation between different proteins in the invasive and metastatic processes was found. This cooperation, and not just single protein function, may play a more significant role in the poor prognosis of PDAC. Therefore, multi-target therapy against these cooperative networks should be a primary choice in the future.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Proteomics in Thrombosis and Haemostasis

No Abstract.

Application of Proteomics in Cancer: Recent Trends and Approaches for Biomarkers Discovery

Proteomics has become an important field in molecular sciences, as it provides valuable information on the identity, expression levels, and modification of proteins. For example, cancer proteomics unraveled key information in mechanistic studies on tumor growth and metastasis, which has contributed to the identification of clinically applicable biomarkers as well as therapeutic targets. Several cancer proteome databases have been established and are being shared worldwide. Importantly, the integration of proteomics studies with other omics is providing extensive data related to molecular mechanisms and target modulators. These data may be analyzed and processed through bioinformatic pipelines to obtain useful information. The purpose of this review is to provide an overview of cancer proteomics and recent advances in proteomic techniques. In particular, we aim to offer insights into current proteomics studies of brain cancer, in which proteomic applications are in a relatively early stage. This review covers applications of proteomics from the discovery of biomarkers to the characterization of molecular mechanisms through advances in technology. Moreover, it addresses global trends in proteomics approaches for translational research. As a core method in translational research, the continued development of this field is expected to provide valuable information at a scale beyond that previously seen.

The use of proteomics for blood biomarker research in premature infants: a scoping review

Over the last decade, the use of proteomics in the setting of prematurity has increased and has enabled researchers to successfully identify biomarkers for an array of associated morbidities. The objective of this scoping review was to identify the existing literature, as well as any knowledge gaps related to proteomic biomarker discoveries in the setting of prematurity. A scoping review was conducted using PubMed, Embase and Medline databases following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The study selection process yielded a total of 700 records, of which 13 studies were included in this review. Most studies used a tandem Mass Spectrometry (MS/MS) proteomics approach to identify key biomarkers. The corresponding studies identified proteins associated with retinopathy of prematurity (ROP), bronchopulmonary dysplasia (BPD), necrotising enterocolitis (NEC), late onset sepsis (LOS) and gestational age. This scoping review demonstrates the limited use of proteomics to identify biomarkers associated with severe complications of prematurity. Further research is warranted to identify biomarkers of other important morbidities associated with prematurity, such as intraventricular haemorrhage (IVH) and cerebral palsy, and to investigate the mechanisms associated with these outcomes.

Ovarian Cancer: Tumor-Specific Urinary Micro-Peptides Profiling as Potential Biomarkers for Early Diagnosis

Ovarian cancer is the second major lethal gynecologic malignancy in developing countries. This study aimed to characterize urinary micro-peptides as potential diagnostic biomarkers for ovarian cancer. In a prospective, longitudinal and case-controlled study and following informed consent, urine and plasma samples were collected from 112 women with histologically-proven ovarian cancer and 200 apparently healthy age-matched volunteers. Urinary micro-peptides were detected and sequenced using SDS-PAGE and Edman degradation technique. Serum CA125 was detected in less than a quarter (23.2%, 26/112) of patients. One or more urinary micro-peptides were detected in about two thirds of the patients (62.5%, 70/112). A total of 40 patients had three bands (57.1%, 40/70), while two bands (15 and 35 kDa) were detected in 28.6% (20/70) of the patients. Isolated 45 kDa band was seen in 14.3% (10/70). No urinary micro-peptide was detected in the volunteers. The 15 and 35 kDa bands disappeared after 6 months of regular chemotherapy, while the 45 kDa band persisted in 2.9% (2/70) of the patients after treatment. The micro-peptides were identified as: Catalase (45 kDa), α-1 Acid Glycoprotein (35 kDa) and Peroxiredoxin-2 (15 kDa). Urinary catalase, α-1 Acid Glycoprotein and Peroxiredoxin-2 can be useful biomarkers for early detection and treatment response of ovarian cancer.

Proteomic analysis enables distinction of early- versus advanced-stage lung adenocarcinomas

Background

A gel‐free proteomic approach was utilized to perform in‐depth tissue protein profiling of lung adenocarcinoma (ADC) and normal lung tissues from early and advanced stages of the disease. The long‐term goal of this study is to generate a large‐scale, label‐free proteomics dataset from histologically well‐classified lung ADC that can be used to increase further our understanding of disease progression and aid in identifying novel biomarkers.

Methods and results

Cases of early‐stage (I‐II) and advanced‐stage (III‐IV) lung ADCs were selected and paired with normal lung tissues from 22 patients. The histologically and clinically stratified human primary lung ADCs were analyzed by liquid chromatography‐tandem mass spectrometry. From the analysis of ADC and normal specimens, 4863 protein groups were identified. To examine the protein expression profile of ADC, a peak area‐based quantitation method was used. In early‐ and advanced‐stage ADC, 365 and 366 proteins were differentially expressed, respectively, between normal and tumor tissues (adjusted P‐value < .01, fold change ≥ 4). A total of 155 proteins were dysregulated between early‐ and advanced‐stage ADCs and 18 were suggested as early‐specific stage ADC. In silico functional analysis of the upregulated proteins in both tumor groups revealed that most of the enriched pathways are involved in mRNA metabolism. Furthermore, the most overrepresented pathways in the proteins that were unique to ADC are related to mRNA metabolic processes.

Conclusions

Further analysis of these data may provide an insight into the molecular pathways involved in disease etiology and may lead to the identification of biomarker candidates and potential targets for therapy. Our study provides potential diagnostic biomarkers for lung ADC and novel stage‐specific drug targets for rational intervention.

The Relevance of Mass Spectrometry Analysis for Personalized Medicine through Its Successful Application in Cancer "Omics"

Mass spectrometry (MS) is an essential analytical technology on which the emerging omics domains; such as genomics; transcriptomics; proteomics and metabolomics; are based. This quantifiable technique allows for the identification of thousands of proteins from cell culture; bodily fluids or tissue using either global or targeted strategies; or detection of biologically active metabolites in ultra amounts. The routine performance of MS technology in the oncological field provides a better understanding of human diseases in terms of pathophysiology; prevention; diagnosis and treatment; as well as development of new biomarkers; drugs targets and therapies. In this review; we argue that the recent; successful advances in MS technologies towards cancer omics studies provides a strong rationale for its implementation in biomedicine as a whole.

Analytical validation of a novel multi-analyte plasma test for lung nodule characterization

BACKGROUND

In the National Lung Screening Trial, 96.4% of nodules had benign etiology. To avoid unnecessary actions and exposure to harm, individuals with benign disease must be identified. We describe herein the analytical validation of a multi-analyte immunoassay for characterizing the risk that a lung nodule found on CT is malignant. Those at lower risk may be considered for serial surveillance to avoid unnecessary and potentially harmful procedures. While those nodules characterized at higher risk may be appropriate for more aggressive actions.

OBJECTIVE

To validate the analytical performance of multiplexed plasma protein assays used in a novel test for lung nodule characterization.

METHODS

A multiplexed immunoassay panel for the measurement of plasma proteins in current smokers who present with a lung nodule on CT scan was evaluated in a clinical testing laboratory. Assay analytical sensitivity, reproducibility, precision, and recovery of Epidermal Growth Factor Receptor (EGFR), Prosurfactant protein B (ProSB), and Tissue Inhibitor of Metalloproteinases 1 (TIMP1) from human EDTA plasma samples were evaluated across multiple runs, lots, and technicians. Interfering substances and sample pre-analytical storage conditions were evaluated for their effect on analyte recovery. The lung nodule risk score reproducibility was assessed across multiple lots.

RESULTS

The assay sensitivities were 0.10 ng/mL EGFR, 0.02 ng/mL ProSB, and 0.29 ng/mL TIMP1 with over three orders of magnitude in the assay dynamic ranges. The assays and analytes are robust to pre-analytical sample handling and the plasma can be stored for up to 4 days at 4°C either when freshy collected or thawed after long-term storage at -80°C. Total imprecision after 20 days of testing remained under 9% for all three assays. Risk score variability remained within a ± 10% risk score range.

CONCLUSIONS

The three protein assays comprising the multi-analyte plasma test for lung nodule characterization performed quite acceptably in a clinical laboratory.

Risk assessment for indeterminate pulmonary nodules using a novel, plasma-protein based biomarker assay

BACKGROUND

The increase in lung cancer screening is intensifying the need for a noninvasive test to characterize the many indeterminate pulmonary nodules (IPN) discovered. Correctly identifying non-cancerous nodules is needed to reduce overdiagnosis and overtreatment. Alternatively, early identification of malignant nodules may represent a potentially curable form of lung cancer.

OBJECTIVE

To develop and validate a plasma-based multiplexed protein assay for classifying IPN by discriminating between those with a lung cancer diagnosis established pathologically and those found to be clinically and radiographically stable for at least one year.

METHODS

Using a novel technology, we developed assays for plasma proteins associated with lung cancer into a panel for characterizing the risk that an IPN found on chest imaging is malignant. The assay panel was evaluated with a cohort of 277 samples, all from current smokers with an IPN 4-30 mm. Subjects were divided into training and test sets to identify a Support Vector Machine (SVM) model for risk classification containing those proteins and clinical factors that added discriminatory information to the Veteran's Affairs (VA) Clinical Factors Model. The algorithm was then evaluated in an independent validation cohort.

RESULTS

Among the 97 validation study subjects, 68 were grouped as having intermediate risk by the VA model of which the SVM model correctly identified 44 (65%) of these intermediate-risk samples as low (n=16) or high risk (n=28). The SVM model negative predictive value (NPV) was 94% and its sensitivity was 94%.

CONCLUSION

The performance of the novel plasma protein biomarker assay supports its use as a noninvasive risk assessment aid for characterizing IPN. The high NPV of the SVM model suggests its application as a rule-out test to increase the confidence of providers to avoid aggressive interventions for their patients for whom the VA model result is an inconclusive, intermediate risk.

From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology

Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.

Exploring the Potential of Data-Independent Acquisition Proteomics Using Untargeted All-Ion Quantitation: Application to Tumor Subtype Diagnosis

Maximizing the recovery of meaningful biological information can facilitate proteomics-guided early detection and precise treatment of diseases. However, the conventional protein and peptide level targeted quantification of untargeted data independent acquisition (DIA) such as sequential window acquisition of all theoretical spectra (SWATH) is not necessarily descriptive of all information. Untargeted all-ion quantification theoretically could retrieve more features in SWATH digital maps by circumventing the initial identification process but is intrinsically susceptible to errors because of the extreme complexity of proteome samples and the poor selectivity of a single ion. In this study, we optimized and applied the untargeted all-ion quantification of SWATH data to differentiate tumor subtypes. Large peptides and low abundant peptides benefited more from untargeted all-ion quantification. Top-ranked significant ions were linked to their corresponding ion envelops, where multiple correlated ions were used for measurement and only ion envelopes containing at least three ions with consistent intensity ratio were kept as refined differentiating features. Multivariate statistical analysis revealed that for the tested data set, the refined markers discovered by untargeted SWATH analysis showed comparable diagnostic power to protein and peptide markers. Limitations and benefits of the approach are further discussed.

Tissue and plasma proteomics for early stage cancer detection

The pursuit of novel and effective biomarkers is essential in the struggle against cancer, which is a leading cause of mortality worldwide. Here we discuss the relative advantages and disadvantages of the most frequently used proteomics techniques, concentrating on the latest advances and application of tissue and plasma proteomics for novel cancer biomarker discovery.

[Omics technologies in diagnostics of lung adenocarcinoma]

To date lung adenocarcinoma (LAC) is the most common type of lung cancer. Numerous studies on LAC biology resulted in identification of crucial mutations in protooncogenes and activating neoplastic transformation pathways. Therapeutic approaches that significantly increase the survival rate of patients with LAC of different etiology have been developed and introduced into clinical practice. However, the main problem in the treatment of LAC is early diagnosis, taking into account both factors and mechanisms responsible in tumor initiation and progression. Identification of a wide biomarker repertoire with high specificity and reliability of detection appears to be a solution to this problem. In this context, proteins with differential expression in normal and pathological condition, suitable for detection in biological fluids are the most promising biomarkers. In this review we have analyzed literature data on studies aimed at search of LAC biomarkers. The major attention has been paid to protein biomarkers as the most promising and convenient subject of clinical diagnosis. The review also summarizes existing knowledge on posttranslational modifications, splice variants, isoforms, as well as model systems and transcriptome changes in LAC.

The role of biomarkers in the management of epithelial ovarian cancer

INTRODUCTION

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

The role of biomarkers in the management of epithelial ovarian cancer

INTRODUCTION

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

The role of biomarkers in the management of epithelial ovarian cancer

INTRODUCTION

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

Ayurvedic concept of Shatkriyakala: a traditional knowledge of cancer pathogenesis and therapy

The term Kriyakala refers to the recognition of the stage of a disease's progress, which helps to determine appropriate measure to correct the imbalance in Doshas (biological factors). It is a compound expression, comprised of Kriya and Kala, where Kriya means the choice to treatment (medicine, food and daily-routine) used to improve the disturbance in Doshas, and Kala refers to the stage of progress of a disease. Sushruta, an ancient Indian surgeon, has described the concept of Kriyakala in Varnaprashnadhyaya, an ancient Vedic Sanskrit text, which seeks to explain the incidence of Varnas in terms of Doshic disturbances. Varna, in modern parlance, may be described as an inflammatory process that may lead ulceration and chronic inflammation, promoting all stages of carcinogenesis. Abnormal interactions between Prakriti (genotype) and environmental factors vitiate the Doshas and impair immunity, which can lead to aberrant cell growth and cancer. Moreover, the interaction between vitiated Doshas and weak Dhatus (body tissues) manifests as cancers of a specific organ. Shatkriyakala (six stages of progress of a disease), on the other hand, provides a framework to assess the cancer and its pathogenesis in different stages. According to Ayurvedic concepts, all cancer therapies treat the affected tissues indirectly by eliminating vitiated Doshas, rejuvenating Dhatus and restoring immunity in cancer patients. The present review describes the six stages of Shatkriyakala in detail, with an emphasis on research areas to validate the concept of Shatkriyakala. This traditional knowledge can be utilized with modern technologies to detect predisposition for cancer or diagnose cancer in its early stages.

Preclinical mouse cancer models: a maze of opportunities and challenges

Significant advances have been made in developing novel therapeutics for cancer treatment, and targeted therapies have revolutionized the treatment of some cancers. Despite the promise, only about five percent of new cancer drugs are approved, and most fail due to lack of efficacy. The indication is that current preclinical methods are limited in predicting successful outcomes. Such failure exacts enormous cost, both financial and in the quality of human life. This Primer explores the current status, promise, and challenges of preclinical evaluation in advanced mouse cancer models and briefly addresses emerging models for early-stage preclinical development.

Risk-reduction strategies to expand radon care planning with vulnerable groups

OBJECTIVES

Radon is the second leading cause of lung cancer in the United States and the leading cause of lung cancer among nonsmokers. Residential radon is the cause of approximately 21,000 U.S. lung cancer deaths each year. Dangerous levels of radon are just as likely to be found in low-rise apartments and townhomes as single-family homes in the same area. The preferred radon mitigation strategy can be expensive and requires structural modifications to the home. The public health nurse (PHN) needs a collection of low-cost alternatives when working with low-income families or families who rent their homes.

METHOD

A review of the literature was performed to identify evidence-based methods to reduce radon risk with vulnerable populations.

RESULTS

Fourteen recommendations for radon risk reduction were categorized into four strategies. Nine additional activities for raising awareness and increasing testing were also included.

DISCUSSION

The results pair the PHN with practical interventions and the underlying rationale to develop radon careplans with vulnerable families across housing types. The PHN has both the competence and the access to help families reduce their exposure to this potent carcinogen.

Nanoproteomics enabling personalized nanomedicine

Nucleic Acid Programmable Protein Arrays utilize a complex mammalian cell free expression system to produce proteins in situ. In alternative to fluorescent-labeled approaches a new label free method, emerging from the combined utilization of three independent and complementary nanotechnological approaches, appears capable to analyze protein function and protein-protein interaction in studies promising for personalized medicine. Quartz Micro Circuit nanogravimetry, based on frequency and dissipation factor, mass spectrometry and anodic porous alumina overcomes indeed the limits of correlated fluorescence detection plagued by the background still present after extensive washes. This could be further optimized by a homogeneous and well defined bacterial cell free expression system capable to realize the ambitious objective to quantify the regulatory protein networks in humans. Implications for personalized medicine of the above label free protein array using different test genes proteins are reported.