Predictive molecular pathology and its role in targeted cancer therapy: a review focussing on clinical relevance

Digital counting of tissue cells for molecular analysis: the QuANTUM pipeline

The estimation of tumor cellular fraction (TCF) is a crucial step in predictive molecular pathology, representing an entry adequacy criterion also in the next-generation sequencing (NGS) era. However, heterogeneity of quantification practices and inter-pathologist variability hamper the robustness of its evaluation, stressing the need for more reliable results. Here, 121 routine histological samples from non-small cell lung cancer (NSCLC) cases with complete NGS profiling were used to evaluate TCF interobserver variability among three different pathologists (pTCF), developing a computational tool (cTCF) and assessing its reliability vs ground truth (GT) tumor cellularity and potential impact on the final molecular results. Inter-pathologist reproducibility was fair to good, with overall Wk ranging between 0.46 and 0.83 (avg. 0.59). The obtained cTCF was comparable to the GT (p = 0.129, 0.502, and 0.130 for surgical, biopsies, and cell block, respectively) and demonstrated good reliability if elaborated by different pathologists (Wk = 0.9). Overall cTCF was lower as compared to pTCF (30 ± 10 vs 52 ± 19, p < 0.001), with more cases < 20% (17, 14%, p = 0.690), but none containing < 100 cells for the algorithm. Similarities were noted between tumor area estimation and pTCF (36 ± 29, p < 0.001), partly explaining variability in the human assessment of tumor cellularity. Finally, the cTCF allowed a reduction of the copy number variations (CNVs) called (27 vs 29, - 6.9%) with an increase of effective CNVs detection (13 vs 7, + 85.7%), some with potential clinical impact previously undetected with pTCF. An automated computational pipeline (Qupath Analysis of Nuclei from Tumor to Uniform Molecular tests, QuANTUM) has been created and is freely available as a QuPath extension. The computational method used in this study has the potential to improve efficacy and reliability of TCF estimation in NSCLC, with demonstrated impact on the final molecular results.

Globalization of a telepathology network with artificial intelligence applications in Colombia: The GLORIA program study protocol

In Colombia, cancer is recognized as a high-cost pathology by the national government and the Colombian High-Cost Disease Fund. As of 2020, the situation is most critical for adult cancer patients, particularly those under public healthcare and residing in remote regions of the country. The highest lag time for a diagnosis was observed for cervical cancer (79.13 days), followed by prostate (77.30 days), and breast cancer (70.25 days). Timely and accurate histopathological reporting plays a vital role in the diagnosis of cancer. In recent years, digital pathology has been globally implemented as a technological tool in two main areas: telepathology (TP) and computational pathology. TP has been shown to improve rapid and timely diagnosis in anatomic pathology by facilitating interaction between general laboratories and specialized pathologists worldwide through information and telecommunication technologies. Computational pathology provides diagnostic and prognostic assistance based on histopathological patterns, molecular, and clinical information, aiding pathologists in making more accurate diagnoses. We present the study protocol of the GLORIA digital pathology network, a pioneering initiative, and national grant-approved program aiming to design and pilot a Colombian digital pathology transformation focused on TP and computational pathology, in response to the general needs of pathology laboratories for diagnosing complex malignant tumors. The study protocol describes the design of a TP network to expand oncopathology services across all Colombian regions. It also describes an artificial intelligence proposal for lung cancer, one of Colombia's most prevalent cancers, and a freely accessible national histopathological image database to facilitate image analysis studies.

Glyoxal acid-free (GAF) histological fixative is a suitable alternative to formalin: results from an open-label comparative non-inferiority study

Formalin, an aqueous solution of formaldehyde, has been the gold standard for fixation of histological samples for over a century. Despite its considerable advantages, growing evidence points to objective toxicity, particularly highlighting its carcinogenicity and mutagenic effects. In 2016, the European Union proposed a ban, but a temporary permission was granted in consideration of its fundamental role in the medical-diagnostic field. In the present study, we tested an innovative fixative, glyoxal acid-free (GAF) (a glyoxal solution deprived of acids), which allows optimal tissue fixation at structural and molecular level combined with the absence of toxicity and carcinogenic activity. An open-label, non-inferiority, multicentric trial was performed comparing fixation of histological specimens with GAF fixative vs standard phosphate-buffered formalin (PBF), evaluating the morphological preservation and the diagnostic value with four binary score questions answered by both the central pathology reviewer and local center reviewers. The mean of total score in the GAF vs PBF fixative groups was 3.7 ± 0.5 vs 3.9 ± 0.3 for the central reviewer and 3.8 ± 0.5 vs 4.0 ± 0.1 for the local pathologist reviewers, respectively. In terms of median value, similar results were observed between the two fixative groups, with a median value of 4.0. Data collected indicate the non-inferiority of GAF as compared to PBF for all organs tested. The present clinical performance study, performed following the international standard for performance evaluation of in vitro diagnostic medical devices, highlights the capability of GAF to ensure both structural preservation and diagnostic value of the preparations.

Multimodal data fusion for cancer biomarker discovery with deep learning

Technological advances now make it possible to study a patient from multiple angles with high-dimensional, high-throughput multi-scale biomedical data. In oncology, massive amounts of data are being generated ranging from molecular, histopathology, radiology to clinical records. The introduction of deep learning has significantly advanced the analysis of biomedical data. However, most approaches focus on single data modalities leading to slow progress in methods to integrate complementary data types. Development of effective multimodal fusion approaches is becoming increasingly important as a single modality might not be consistent and sufficient to capture the heterogeneity of complex diseases to tailor medical care and improve personalised medicine. Many initiatives now focus on integrating these disparate modalities to unravel the biological processes involved in multifactorial diseases such as cancer. However, many obstacles remain, including lack of usable data as well as methods for clinical validation and interpretation. Here, we cover these current challenges and reflect on opportunities through deep learning to tackle data sparsity and scarcity, multimodal interpretability, and standardisation of datasets.

A comprehensive tool for tumor precision medicine with pharmaco-omics data analysis

Background: Cancer precision medicine is an effective strategy to fight cancers by bridging genomics and drug discovery to provide specific treatment for patients with different genetic characteristics. Although some public databases and modelling frameworks have been developed through studies on drug response, most of them only considered the ramifications of the drug on the cell line and the effects on the patient still require a huge amount of work to integrate data from various databases and calculations, especially concerning precision treatment. Furthermore, not only efficacy but also the adverse effects of drugs on patients should be taken into account during cancer treatment. However, the adverse effects as essential indicators of drug safety assessment are always neglected. Method: A holistic estimation explores various drugs' efficacy levels by calculating their potency both in reversing and enhancing cancer-associated gene expression change. And a method for bridging the gap between cell culture and living tissue estimates the effectiveness of a drug on individual patients through the mappings of various cell lines to each person according to their genetic mutation similarities. Result: We predicted the efficacy of FDA-recommended drugs, taking into account both efficacy and toxicity, and obtained consistent results. We also provided an intuitive and easy-to-use web server called DBPOM (http://www.dbpom.net/, a comprehensive database of pharmaco-omics for cancer precision medicine), which not only integrates the above methods but also provides calculation results on more than 10,000 small molecule compounds and drugs. As a one-stop web server, clinicians and drug researchers can also analyze the overall effect of a drug or a drug combination on cancer patients as well as the biological functions that they target. DBPOM is now public, free to use with no login requirement, and contains all the data and code. Conclusion: Both the positive and negative effects of drugs during precision treatment are essential for practical application of drugs. DBPOM based on the two effects will become a vital resource and analysis platform for drug development, drug mechanism studies and the discovery of new therapies.

Comparative liquid chromatography/tandem mass spectrometry lipidomics analysis of macaque heart tissue flash-frozen or embedded in optimal cutting temperature polymer (OCT): Practical considerations

RATIONALE

Biobanks of patient tissues have emerged as essential resources in biomedical research. Optimal cutting temperature compound (OCT) blends have shown to provide stability to the embedded tissue and are compatible with spectroscopic methods, such as infrared (IR) and Raman spectroscopy. Data derived from omics-methods are only useful if tissue damage caused by storage in OCT blends is minimal and well understood. In this context, we investigated the suitability of OCT storage for heart tissue destined for liquid chromatography/tandem mass spectrometry (LC/MS/MS) lipidomic studies.

METHODS

To determine the compatibility of OCT storage with LC/MS/MS lipidomics studies. The lipid profiles of macaque heart tissue snap-frozen in liquid nitrogen or stored in an OCT blend were evaluated.

RESULTS

We have evaluated a lipid extraction protocol suitable for OCT-embedded tissue that is compatible with LC/MS/MS. We annotated and evaluated the profiles of 306 lipid species from tissues stored in OCT or liquid nitrogen. For most of the lipid species (95.4%), the profiles were independent of the storage conditions. However, 4.6% of the lipid species; mainly plasmalogens, were affected by the storage method.

CONCLUSIONS

This study shows that OCT storage is compatible with LC-MS/MS lipidomics of heart tissue, facilitating the use of biobanked tissue samples for future studies.

Development of Methods to Extract RNA From Archived Pediatric Needle Liver Biopsies to Produce Sequencing Data

ABSTRACT

Genetic susceptibility has been proposed as etiopathogenic in several pediatric liver diseases including autoimmune hepatitis (AIH). High throughput sequencing (HTPS) has been applied to archived needle liver biopsies obtained from adults but rarely to pediatric biopsies. For conclusive diagnosis of AIH, most subjects have an initial formalin-fixed paraffin embedded (FFPE) needle liver biopsy that is eventually archived and may be stored for decades.

OBJECTIVE

Our goal was to develop methods to utilize tissue from archived needle liver biopsies for extraction of RNA sufficient to produce HTPS data.

METHODS

We extracted total RNA from 45 FFPE needle liver biopsy samples (24 AIH type 1 patients and 21 controls [ages 15_11 and 19_10]; biopsy storage time 0.5-20 years) and constructed cDNA libraries that were then sequenced on an Illumina HiSeq2000 platform.

RESULTS

Forty (89%) of the libraries produced high-quality sequences for further analyses. The average number of sequences obtained per library from HTPS was 55,136,519 (range 14,914,291-184,027,499). There was a significant inverse relationship between the number of human reads obtained and the age of the specimen (P < 2_10_7). It was possible to classify more than 90% of the reads as known genes in samples that had been stored for less than 10 years.

CONCLUSIONS

Archived needle liver biopsies can be used for sequence based interrogation of the etiologic origins of complex liver diseases of young subjects, such as AIH.

Neurotrophic tyrosine kinase inhibitors: A review of implications for patients, clinicians and healthcare services

Neurotrophic tyrosine receptor kinase (NTRK) inhibitors represent the latest advancement as a treatment option in targeted therapies for malignant disease. NTRK gene fusions involving NTRK1, 2 or 3 are implicated as genetics drivers for a number of tumour types which arise within adult and paedatric patients. NTRK inhibitors (Larotrectinib and Entrectinib) are effective agents which have demonstrated clinical benefit in the treatment of NTRK fusion positive solid tumours. Larotrectinib represents the first targeted agent to receive approval from international authorisation and commissioning bodies for the treatment of a specific genetic expression indiscriminate of the site from which the tumour has arisen. As such NTRK inhibitors could pave the way for international healthcare bodies to adopt a similar approach for future targeted therapies thereby altering the manner in which healthcare providers and patients are able to access and utilise innovative, targeted treatment options in future. The potential implications of this new approach are likely to impact upon several aspects of the traditional authorisation and commissioning pathways with potential changes to the design of clinical trials, the review and approval process by regulatory bodies and immunohistopathology services.

Genetic Markers in Lung Cancer Diagnosis: A Review

Lung cancer is the most often diagnosed cancer in the world and the most frequent cause of cancer death. The prognosis for lung cancer is relatively poor and 75% of patients are diagnosed at its advanced stage. The currently used diagnostic tools are not sensitive enough and do not enable diagnosis at the early stage of the disease. Therefore, searching for new methods of early and accurate diagnosis of lung cancer is crucial for its effective treatment. Lung cancer is the result of multistage carcinogenesis with gradually increasing genetic and epigenetic changes. Screening for the characteristic genetic markers could enable the diagnosis of lung cancer at its early stage. The aim of this review was the summarization of both the preclinical and clinical approaches in the genetic diagnostics of lung cancer. The advancement of molecular strategies and analytic platforms makes it possible to analyze the genome changes leading to cancer development-i.e., the potential biomarkers of lung cancer. In the reviewed studies, the diagnostic values of microsatellite changes, DNA hypermethylation, and p53 and KRAS gene mutations, as well as microRNAs expression, have been analyzed as potential genetic markers. It seems that microRNAs and their expression profiles have the greatest diagnostic potential value in lung cancer diagnosis, but their quantification requires standardization.

Self-digitization chip for quantitative detection of human papillomavirus gene using digital LAMP

Digital nucleic acid amplification and detection methods provide excellent sensitivity and specificity and allow absolute quantification of target nucleic acids. Isothermal methods such as digital loop-mediated isothermal amplification (digital LAMP) have potential for use in rapid disease diagnosis in low-resource settings due to their speed and lack of thermal cycling. We previously developed a self-digitization (SD) chip, a simple microfluidics device that automatically digitizes a sample into an array of nanoliter wells, for use in digital LAMP. In this work, we improve the SD chip design to increase sample loading efficiency, speed, and completeness, and test a range of well volumes and numbers. We demonstrate the diagnostic capability of this platform by applying it to quantifying human papillomavirus 18 gene.

Preliminary exploration of potential molecular therapeutic targets in recurrent and metastatic parathyroid carcinomas

Parathyroid carcinoma (PC) is a rare endocrine malignancy. Surgical resection is curative for local lesions, while effective therapies are lacking for recurrent or metastatic PCs. To study whether targeted therapies could be applied in recurrent or metastatic PCs, potential therapeutic targets were identified with next-generation sequencing (NGS). DNA was extracted from formalin-fixed, paraffin-embedded (FFPE) sections from 19 recurrent or metastatic PC samples. A panel of 560 genes was sequenced with NGS to identify genomic alterations at an average sequencing depth of 581×. In total, 190 genomic alterations were identified. Nine PC samples (47%) harbored at least one potentially actionable genomic alteration including in the after genes: ROS1 (5/19; 26%), PTEN (3/19; 16%), TSC1 (2/19; 11%), PIK3CA (1/19; 5%), AKT1 (1/19; 5%), MTOR (1/19; 5%), ERBB2 (1/19; 5%), NTRK1 (1/19; 5%), IDH1 (1/19; 5%) and FGFR3 (1/19; 5%). CDC73 mutations were detected in 9/19 (47%) PC samples. Additional recurrent genomic alterations were identified in MSH2 (15/19; 79%), AR (9/19; 47%), BCR (8/19; 42%), SLC45A3 (6/19; 32%), MAGI1 (5/19; 26%), ZNF521 (4/19; 21%), KMT2C (4/19; 21%) and NOTCH4 (4/19; 21%). Our study identified a relatively high frequency of potentially actionable genomic alterations in PC patients in a Chinese population for the first time. A series of recurrent mutant genes was detected as well. Our study contributes to both the selection of novel targeted therapies for PC and further molecular understanding of this refractory malignancy.

Are We There Yet? How and When Specific Biotechnologies Will Improve Human Health

Patient X: A 67-year-old Caucasian man slips on a patch of ice. He has abrasions to his hands and has sustained significant damage to his hip. At the emergency room, he informs clinicians he takes atorvastatin, metformin, and glimepiride to treat hypertension and Type 2 Diabetes Mellitus (T2DM). X-rays reveal a fractured hip, which will require total hip replacement surgery.

Molecular Diagnostics in Pathology: Time for a Next-Generation Pathologist?

CONTEXT

- Comprehensive molecular investigations of mainstream carcinogenic processes have led to the use of effective molecular targeted agents in most cases of solid tumors in clinical settings.

OBJECTIVE

- To update readers regarding the evolving role of the pathologist in the therapeutic decision-making process and the introduction of next-generation technologies into pathology practice.

DATA SOURCES

- Current literature on the topic, primarily sourced from the PubMed (National Center for Biotechnology Information, Bethesda, Maryland) database, were reviewed.

CONCLUSIONS

- Adequate evaluation of cytologic-based and tissue-based predictive diagnostic biomarkers largely depends on both proper pathologic characterization and customized processing of biospecimens. Moreover, increased requests for molecular testing have paralleled the recent, sharp decrease in tumor material to be analyzed-material that currently comprises cytology specimens or, at minimum, small biopsies in most cases of metastatic/advanced disease. Traditional diagnostic pathology has been completely revolutionized by the introduction of next-generation technologies, which provide multigene, targeted mutational profiling, even in the most complex of clinical cases. Combining traditional and molecular knowledge, pathologists integrate the morphological, clinical, and molecular dimensions of a disease, leading to a proper diagnosis and, therefore, the most-appropriate tailored therapy.

Cancer diagnostics: The journey from histomorphology to molecular profiling

Although histomorphology has made significant advances into the understanding of cancer etiology, classification and pathogenesis, it is sometimes complicated by morphologic ambiguities, and other shortcomings that necessitate the development of ancillary tests to complement its diagnostic value. A new approach to cancer patient management consists of targeting specific molecules or gene mutations in the cancer genome by inhibitory therapy. Molecular diagnostic tests and genomic profiling methods are increasingly being developed to identify tumor targeted molecular profile that is the basis of targeted therapy. Novel targeted therapy has revolutionized the treatment of gastrointestinal stromal tumor, renal cell carcinoma and other cancers that were previously difficult to treat with standard chemotherapy. In this review, we discuss the role of histomorphology in cancer diagnosis and management and the rising role of molecular profiling in targeted therapy. Molecular profiling in certain diagnostic and therapeutic difficulties may provide a practical and useful complement to histomorphology and opens new avenues for targeted therapy and alternative methods of cancer patient management.

The Importance of Biopsy in the Era of Molecular Medicine

Recent advances in the molecular characterization of cancers have triggered interest in developing a new taxonomy of disease in oncology with the goal of using the molecular profile of a patient's tumor to predict response to treatment. Image-guided needle biopsy is central to this "precision medicine" effort. In this review, we first discuss the current role of biopsy in relation to clinical examples of molecular medicine. We then outline important bottlenecks to the advancement of precision medicine and highlight the potential role of image-guided biopsy to address these challenges.

In situ assembly of active surface-enhanced Raman scattering substrates via electric field-guided growth of dendritic nanoparticle structures

Surface-enhanced Raman scattering (SERS) can provide ultrasensitive detection of chemical and biological analytes down to the level of a single molecule. The need for costly, nanostructured, noble-metal substrates, however, poses a major obstacle in the widespread application of the method. Here we present for the first time a novel type of metallic nanostructured substrates that, not only exhibit a remarkable SERS activity, but are also produced in a facile, cost-effective and nanofabrication-free manner. The substrates are formed through an electric field-guided assembly process of silver nanocolloids, which results in extended and interconnected dendritic nanoparticle structures with a high density of "hot spots". A unique and significant performance attribute of these nanostructures is their ability to also function as concentration amplification devices, thereby further enhancing their analyte detection efficiency. This major advantage against conventional SERS substrates is illustrated experimentally here with the concentration and detection of proteins from solution. Low limits of detection for illicit drugs, food contaminants and pesticides in relevant matrices are also demonstrated. The SERS-active dendrites are reusable and can be removed and replaced in a few minutes. The SERS substrates presented herein constitute a significant advance towards more effective and less expensive diagnostic tools.

In Situ Metabolomics in Cancer by Mass Spectrometry Imaging

Metabolomics is a rapidly evolving and a promising research field with the expectation to improve diagnosis, therapeutic treatment prediction, and prognosis of particular diseases. Among all techniques used to assess the metabolome in biological systems, mass spectrometry imaging is the method of choice to qualitatively and quantitatively analyze metabolite distribution in tissues with a high spatial resolution, thus providing molecular data in relation to cancer histopathology. The technique is ideally suited to study tissues molecular content and is able to provide molecular biomarkers or specific mass signatures which can be used in classification or the prognostic evaluation of tumors. Recently, it was shown that FFPE tissue samples are also suitable for metabolic analyses. This progress in methodology allows access to a highly valuable resource of tissues believed to widen and strengthen metabolic discovery-driven studies.

Retroviral Replicating Vectors Deliver Cytosine Deaminase Leading to Targeted 5-Fluorouracil-Mediated Cytotoxicity in Multiple Human Cancer Types

Toca 511 is a modified retroviral replicating vector based on Moloney γ-retrovirus with an amphotropic envelope. As an investigational cancer treatment, Toca 511 preferentially infects cancer cells without direct cell lysis and encodes an enhanced yeast cytosine deaminase that converts the antifungal drug 5-fluorocytosine to the anticancer drug, 5-fluorouracil. A panel of established human cancer cell lines, derived from glioblastoma, colon, and breast cancer tissue, was used to evaluate parameters critical for effective anticancer activity. Gene transfer, cytosine deaminase production, conversion of 5-fluorocytosine to 5-fluorouracil, and subsequent cell killing occurred in all lines tested. We observed >50% infection within 25 days in all lines and 5-fluorocytosine LD50 values between 0.02 and 6 μg/ml. Although we did not identify a small number of key criteria, these studies do provide a straightforward approach to rapidly gauge the probability of a Toca 511 and 5-fluorocytosine treatment effect in various cancer indications: a single MTS assay of maximally infected cancer cell lines to determine 5-fluorocytosine LD50. The data suggest that, although there can be variation in susceptibility to Toca 511 and 5-fluorocytosine because of multiple mechanistic factors, this therapy may be applicable to a broad range of cancer types and individuals.

Periodontal CD14 mRNA expression is downregulated in patients with chronic periodontitis and type 2 diabetes

Background

Patients with type 2 diabetes mellitus (T2DM) have increased severity of periodontitis. Toll-like receptor (TLR)4, its co-receptors CD14 and MD-2, and adaptor MyD88 play pivotal roles in lipopolysaccharide (LPS)-triggered tissue inflammation and periodontitis. This study investigated the effects of T2DM and periodontitis on TLR4, CD14, MD-2 and MyD88 mRNA expression in surgically removed periodontal tissues.

Methods

Periodontal tissue specimens were collected from 14 patients without periodontitis and T2DM (Group 1), 15 patients with periodontitis alone (Group 2), and 7 patients with both periodontitis and T2DM (Group 3). The mRNA of TLR4, CD14, MD-2 and MyD88 was quantified using real-time PCR and compared between the groups.

Results

Statistical analysis showed that periodontal expression of CD14 mRNA was significantly reduced across Groups 1, 2 and 3 (p = 0.02) whereas the mRNA expression of TLR4, MD-2 and MyD88 was not significantly different among the groups. Furthermore, when patients in Groups 1 and 2 were combined (n = 22), the CD14 mRNA expression was significantly lower than that in patients of Group 1 (p = 0.04).

Conclusions

CD14 mRNA expression was downregulated across patients with neither periodontitis nor T2DM, patients with periodontitis alone and patients with both diseases, suggesting that CD14 mRNA expression is associated with a favorable host response or subjected to a negative feedback regulation.

Diagnostic procedures for non-small-cell lung cancer (NSCLC): recommendations of the European Expert Group

BACKGROUND

There is currently no Europe-wide consensus on the appropriate preanalytical measures and workflow to optimise procedures for tissue-based molecular testing of non-small-cell lung cancer (NSCLC). To address this, a group of lung cancer experts (see list of authors) convened to discuss and propose standard operating procedures (SOPs) for NSCLC.

METHODS

Based on earlier meetings and scientific expertise on lung cancer, a multidisciplinary group meeting was aligned. The aim was to include all relevant aspects concerning NSCLC diagnosis. After careful consideration, the following topics were selected and each was reviewed by the experts: surgical resection and sampling; biopsy procedures for analysis; preanalytical and other variables affecting quality of tissue; tissue conservation; testing procedures for epidermal growth factor receptor, anaplastic lymphoma kinase and ROS proto-oncogene 1, receptor tyrosine kinase (ROS1) in lung tissue and cytological specimens; as well as standardised reporting and quality control (QC). Finally, an optimal workflow was described.

RESULTS

Suggested optimal procedures and workflows are discussed in detail. The broad consensus was that the complex workflow presented can only be executed effectively by an interdisciplinary approach using a well-trained team.

CONCLUSIONS

To optimise diagnosis and treatment of patients with NSCLC, it is essential to establish SOPs that are adaptable to the local situation. In addition, a continuous QC system and a local multidisciplinary tumour-type-oriented board are essential.

Epigenetic mechanisms involved in melanoma pathogenesis and chemoresistance

The discovery of highly recurrent mutations in melanoma, such as BRAF(V600E), completely changed the clinical management including therapy of melanoma patients. In the era of Personalized Medicine targeted melanoma therapies showed high response rates, currently evidenced by BRAF inhibitors or immune-stimulating therapies. In addition to genetic biomarkers, epigenetic knowledge in melanoma has undergone a major step forward in recent years. In particular, epigenetics is unveiling new perspectives to fight this disease, providing an encouraging number of DNA methylation based biomarkers that will likely improve patient stratification for prognosis and treatment. In this regard, putative targetable biomarkers or those with predictive value for the outcome of currently applied therapies are promising tools for future precision oncology strategies. In addition, the progress made in genetic and epigenetic profiling technologies and their reconfiguration to real-time clinical screening approaches makes personalized medicine in melanoma an achievable objective in upcoming years.

A 2015 update on predictive molecular pathology and its role in targeted cancer therapy: a review focussing on clinical relevance

In April 2013 our group published a review on predictive molecular pathology in this journal. Although only 2 years have passed many new facts and stimulating developments have happened in diagnostic molecular pathology rendering it worthwhile to present an up-date on this topic. A major technical improvement is certainly given by the introduction of next-generation sequencing (NGS; amplicon, whole exome, whole genome) and its application to formalin-fixed paraffin-embedded (FFPE) tissue in routine diagnostics. Based on this 'revolution' the analyses of numerous genetic alterations in parallel has become a routine approach opening the chance to characterize patients' malignant tumors much more deeply without increasing turn-around time and costs. In the near future this will open new strategies to apply 'off-label' targeted therapies, e.g. for rare tumors, otherwise resistant tumors etc. The clinically relevant genetic aberrations described in this review include mutation analyses of RAS (KRAS and NRAS), BRAF and PI3K in colorectal cancer, KIT or PDGFR alpha as well as BRAF, NRAS and KIT in malignant melanoma. Moreover, we present several recent advances in the molecular characterization of malignant lymphoma. Beside the well-known mutations in NSCLC (EGFR, ALK) a number of chromosomal aberrations (KRAS, ROS1, MET) have become relevant. Only very recently has the clinical need for analysis of BRCA1/2 come up and proven as a true challenge for routine diagnostics because of the genes' special structure and hot-spot-free mutational distribution. The genetic alterations are discussed in connection with their increasingly important role in companion diagnostics to apply targeted drugs as efficient as possible. As another aspect of the increasing number of druggable mutations, we discuss the challenges personalized therapies pose for the design of clinical studies to prove optimal efficacy particularly with respect to combination therapies of multiple targeted drugs and conventional chemotherapy. Such combinations would lead to an extremely high complexity that would hardly be manageable by applying conventional study designs for approval, e.g. by the FDA or EMA. Up-coming challenges such as the application of methylation assays and proteomic analyses on FFPE tissue will also be discussed briefly to open the door towards the ultimate goal of reading a patients' tissue as 'deeply' as possible. Although it is yet to be shown, which levels of biological information are most informative for predictive pathology, an integrated molecular characterization of tumors will likely offer the most comprehensive view for individualized therapy approaches. To optimize cancer treatment we need to understand tumor biology in much more detail on morphological, genetic, proteomic as well as epigenetic grounds. Finally, the complex challenges on the level of drug design, molecular diagnostics, and clinical trials make necessary a close collaboration among academic institutions, regulatory authorities and pharmaceutical companies.

Endorsing good quality assurance practices in molecular pathology: risks and recommendations for diagnostic laboratories and external quality assessment providers

Quality assurance is an indispensable element in a molecular diagnostic laboratory. The ultimate goal is to warrant patient safety. Several risks that can compromise high quality procedures are at stake, from sample collection to the test performed by the laboratory, the reporting of test results to clinicians, and the organization of effective external quality assessment schemes. Quality assurance should therefore be safeguarded at each level and should imply a holistic multidisciplinary approach. This review aims to provide an overview of good quality assurance practices and discusses certain risks and recommendations to promote and improve quality assurance for both diagnostic laboratories and for external quality assessment providers. The number of molecular targets is continuously rising, and new technologies are evolving. As this poses challenges for clinical implementation and increases the demand for external quality assessment, the formation of an international association for improving quality assurance in molecular pathology is called for.

National Institutes of Health: a catalyst in advancing regenerative medicine science into practice

The stem cell domain of the regenerative medicine field has seen fundamental changes initiated by seminal discoveries in cell biology, genetic engineering, and whole genome sequencing. Many of these discoveries were funded in part by the National Institutes of Health (NIH), and the NIH remains a leader in supporting research in the United States. However, as the field has developed, the NIH has responded proactively to identify roadblocks and to develop solutions that will accelerate translation of basic discoveries to the clinical setting. These activities range from organizing specialized workshops and coordinating activities among international organizations and the different arms of the government to funding small-scale industry. In addition, the NIH has been a key driver in providing needed infrastructure in areas in which the private sector has been unable to, or does not believe it can, invest. These activities of the NIH are as important as its traditional funding role, and I believe they have contributed to the innovation and rapid pace of discovery in this field.

Molecular pathology - the value of an integrative approach

Molecular Pathology (MP) is at the heart of modern diagnostics and translational research, but the controversy on how MP is best developed has not abated. The lack of a proper model or trained pathologists to support the diagnostic and research missions makes MP a rare commodity overall. Here we analyse the scientific and technology areas, in research and diagnostics, which are encompassed by MP of solid tumours; we highlight the broad overlap of technologies and analytical capabilities in tissue research and diagnostics; and we describe an integrated model that rationalizes technical know-how and pathology talent for both. The model is based on a single, accredited laboratory providing a single standard of high-quality for biomarker discovery, biomarker validation and molecular diagnostics.

Identification of one-electron reductases that activate both the hypoxia prodrug SN30000 and diagnostic probe EF5

SN30000 is a second-generation benzotriazine-N-oxide hypoxia-activated prodrug scheduled for clinical trial. Previously we showed that covalent binding of the hypoxia probe EF5 predicts metabolic activation of SN30000 in a panel of cancer cell lines under anoxia, suggesting that they are activated by the same reductases. However the identity of these reductases is unknown. Here, we test whether forced expression of nine oxidoreductases with known or suspected roles in bioreductive prodrug metabolism (AKR1C3, CYB5R3, FDXR, MTRR, NDOR1, NOS2A, NQO1, NQO2 and POR) enhances oxic or anoxic reduction of SN30000 and EF5 by HCT116 cells. Covalent binding of (14)C-EF5 and reduction of SN30000 to its 1-oxide and nor-oxide metabolites was highly selective for anoxia in all lines, with significantly elevated anoxic metabolism of both compounds in lines over-expressing POR, MTRR, NOS2A or NDOR1. There was a strong correlation between EF5 binding and SN30000 metabolism under anoxia across the cell lines (R(2)=0.84, p=0.0001). Antiproliferative potency of SN30000 under anoxia was increased most strongly by overexpression of MTRR and POR. Transcript abundance in human tumours, evaluated using public domain mRNA expression data, was highest for MTRR, followed by POR, NOS2A and NDOR1, with little variation between tumour types. Immunostaining of tissue microarrays demonstrated variable MTRR protein expression across 517 human cancers with most displaying low expression. In conclusion, we have identified four diflavin reductases (POR, MTRR, NOS2A and NDOR1) capable of reducing both SN30000 and EF5, further supporting use of 2-nitroimidazole probes to predict the ability of hypoxic cells to activate SN30000.

Analytical validation of the PAM50-based Prosigna Breast Cancer Prognostic Gene Signature Assay and nCounter Analysis System using formalin-fixed paraffin-embedded breast tumor specimens

Background

NanoString’s Prosigna™ Breast Cancer Prognostic Gene Signature Assay is based on the PAM50 gene expression signature. The test outputs a risk of recurrence (ROR) score, risk category, and intrinsic subtype (Luminal A/B, HER2-enriched, Basal-like). The studies described here were designed to validate the analytical performance of the test on the nCounter Analysis System across multiple laboratories.

Methods

Analytical precision was measured by testing five breast tumor RNA samples across 3 sites. Reproducibility was measured by testing replicate tissue sections from 43 FFPE breast tumor blocks across 3 sites following independent pathology review at each site. The RNA input range was validated by comparing assay results at the extremes of the specified range to the nominal RNA input level. Interference was evaluated by including non-tumor tissue into the test.

Results

The measured standard deviation (SD) was less than 1 ROR unit within the analytical precision study and the measured total SD was 2.9 ROR units within the reproducibility study. The ROR scores for RNA inputs at the extremes of the range were the same as those at the nominal input level. Assay results were stable in the presence of moderate amounts of surrounding non-tumor tissue (<70% by area).

Conclusions

The analytical performance of NanoString’s Prosigna assay has been validated using FFPE breast tumor specimens across multiple clinical testing laboratories.

Personalized oncology in interventional radiology

As personalized medicine becomes more applicable to oncologic practice, image-guided biopsies will be integral for enabling predictive and pharmacodynamic molecular pathology. Interventional radiology has a key role in defining patient-specific management. Advances in diagnostic techniques, genomics, and proteomics enable a window into subcellular mechanisms driving hyperproliferation, metastatic capabilities, and tumor angiogenesis. A new era of personalized medicine has evolved whereby clinical decisions are adjusted according to a patient's molecular profile. Several mutations and key markers already have been introduced into standard oncologic practice. A broader understanding of personalized oncology will help interventionalists play a greater role in therapy selection and discovery.

Fluorescence in situ hybridization (FISH): an increasingly demanded tool for biomarker research and personalized medicine

Extensive studies of the genetic aberrations related to human diseases conducted over the last two decades have identified recurrent genomic abnormalities as potential driving factors underlying a variety of cancers. Over the time, a series of cutting-edge high-throughput genetic tests, such as microarrays and next-generation sequencing, have been developed and incorporated into routine clinical practice. Although it is a classical low-throughput cytogenetic test, fluorescence in situ hybridization (FISH) does not show signs of fading; on the contrary, it plays an increasingly important role in detecting specific biomarkers in solid and hematologic neoplasms and has therefore become an indispensable part of the rapidly developing field of personalized medicine. In this article, we have summarized the recent advances in FISH application for both de novo discovery and routine detection of chromosomal rearrangements, amplifications, and deletions that are associated with the pathogenesis of various hematopoietic and non-hematopoietic malignancies. In addition, we have reviewed the recent developments in FISH methodology as well.

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

INTRODUCTION

Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.

METHODS

More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer 'stem' cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.

RESULTS

The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.

CONCLUSIONS

With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

The EndoPredict Gene-Expression Assay in Clinical Practice - Performance and Impact on Clinical Decisions

The validated EndoPredict assay is a novel tool to predict the risk of metastases of patients with estrogen receptor positive, HER2 negative breast cancer treated with endocrine therapy alone. It has been designed to integrate genomic and clinical information and includes clinico-pathological factors such as tumor size and nodal status. The test is feasible in a decentral setting in molecular pathology laboratories. In this project, we investigated the performance of this test in clinical practice, and performed a retrospective evaluation of its impact on treatment decisions in breast cancer. During one year, EndoPredict assays from 167 patients could be successfully performed. For retrospective evaluation of treatment decisions, a questionnaire was sent to the clinical partner. Regarding the molecular EP class, samples from 56 patients (33.5%) had a low-risk, whereas 111 patients (66.5%) showed a high-risk gene profile. After integration of the clinicopathological factors the combined clinical and molecular score (EPclin) resulted in a low-risk group of 77 patients (46.4%), while 89 (53.6%) had a high risk EPclin score. The EPclin-based estimated median 10-year-risk for metastases with endocrine therapy alone was 11% for the whole cohort. The median handling time averaged three days (range: 0 to 11 days), 59.3% of the tests could be performed in three or less than three days. Comparison of pre- and post-test therapy decisions showed a change of therapy in 37.7% of patients. 16 patients (12.3%) had a change to an additional chemotherapy while 25.4% of patients (n = 33) changed to an endocrine therapy alone. In 73 patients (56.2%) no change of therapy resulted. In 6.1% of patients (n = 8), the patients did not agree to the recommendation of the tumor board. Our results show that the EndoPredict assay could be routinely performed in decentral molecular pathology laboratories and the results markedly change treatment decisions.