Molecular classification of unknown primary cancer

Spectrum of Findings Seen in Patients With IDH1/2-Mutant Cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma-with a growing incidence rate and poor prognosis-is not an aggressive tumor that is not uncommon. Molecular profiling can reveal actionable aberrations in at least a third of the tumors. This is especially so in the case of intrahepatic cholangiocarcinoma (ICC), where mutations in the isocitrate dehydrogenase 1 and 2 genes (IDH1/2) make up 15%-20% of these tumors. IDH1/2 mutant ICC is a rare disease that has not been adequately reported. To expand the spectrum of findings seen in these patients, we present a single institution case series.

METHODS AND RESULTS

We descriptively characterize the clinical, radiological, and histopathological findings of 12 such patients. IDH1/2 mutant ICC was found in elderly women, with two-thirds of patients having additional co-mutations. Anecdotally, patients who did receive systemic and/or locoregional therapies had long-term durable outcomes.

CONCLUSION

Our findings indicate an increasing need to personalize an approach for these patients with specific molecular alterations. With the advent of the IDH1 inhibitor ivosidenib and other inhibitors in this space, IDH1/2 mutation has both prognostic and predictive value. Our series builds upon the patterns and findings seen in these patients.

High-throughput proteomics and AI for cancer biomarker discovery

Biomarkers are assayed to assess biological and pathological status. Recent advances in high-throughput proteomic technology provide opportunities for developing next generation biomarkers for clinical practice aided by artificial intelligence (AI) based techniques. We summarize the advances and limitations of cancer biomarkers based on genomic and transcriptomic analysis, as well as classical antibody-based methodologies. Then we review recent progresses in mass spectrometry (MS)-based proteomics in terms of sample preparation, peptide fractionation by liquid chromatography (LC) and mass spectrometric data acquisition. We highlight applications of AI techniques in high-throughput clinical studies as compared with clinical decisions based on singular features. This review sets out our approach for discovering clinical biomarkers in studies using proteomic big data technology conjoined with computational and statistical methods.

Evaluating DNA Methylation, Gene Expression, Somatic Mutation, and Their Combinations in Inferring Tumor Tissue-of-Origin

Carcinoma of unknown primary (CUP) is a type of metastatic cancer, the primary tumor site of which cannot be identified. CUP occupies approximately 5% of cancer incidences in the United States with usually unfavorable prognosis, making it a big threat to public health. Traditional methods to identify the tissue-of-origin (TOO) of CUP like immunohistochemistry can only deal with around 20% CUP patients. In recent years, more and more studies suggest that it is promising to solve the problem by integrating machine learning techniques with big biomedical data involving multiple types of biomarkers including epigenetic, genetic, and gene expression profiles, such as DNA methylation. Different biomarkers play different roles in cancer research; for example, genomic mutations in a patient’s tumor could lead to specific anticancer drugs for treatment; DNA methylation and copy number variation could reveal tumor tissue of origin and molecular classification. However, there is no systematic comparison on which biomarker is better at identifying the cancer type and site of origin. In addition, it might also be possible to further improve the inference accuracy by integrating multiple types of biomarkers. In this study, we used primary tumor data rather than metastatic tumor data. Although the use of primary tumors may lead to some biases in our classification model, their tumor-of-origins are known. In addition, previous studies have suggested that the CUP prediction model built from primary tumors could efficiently predict TOO of metastatic cancers (Lal et al., 2013; Brachtel et al., 2016). We systematically compared the performances of three types of biomarkers including DNA methylation, gene expression profile, and somatic mutation as well as their combinations in inferring the TOO of CUP patients. First, we downloaded the gene expression profile, somatic mutation and DNA methylation data of 7,224 tumor samples across 21 common cancer types from the cancer genome atlas (TCGA) and generated seven different feature matrices through various combinations. Second, we performed feature selection by the Pearson correlation method. The selected features for each matrix were used to build up an XGBoost multi-label classification model to infer cancer TOO, an algorithm proven to be effective in a few previous studies. The performance of each biomarker and combination was compared by the 10-fold cross-validation process. Our results showed that the TOO tracing accuracy using gene expression profile was the highest, followed by DNA methylation, while somatic mutation performed the worst. Meanwhile, we found that simply combining multiple biomarkers does not have much effect in improving prediction accuracy.

The role of molecular profiling in the diagnosis and management of metastatic undifferentiated cancer of unknown primary✰: Molecular profiling of metastatic cancer of unknown primary

Cancer of unknown primary (CUP) refers to metastatic tumors for which the primary tumor of origin cannot be determined at the time of diagnosis, despite extensive clinicopathologic investigations. Molecular profiling is increasingly able to predict a probable primary tumor type for CUP when clinicopathologic workup is inconclusive. Numerous studies have explored the use of various molecular profiling techniques for identification of site/tissue of origin of CUP. These techniques include gene expression profiling utilizing microarray, reverse transcriptase polymerase chain reaction, RNA-sequencing, somatic gene mutation profiling with next-generation DNA sequencing, and epigenomics including DNA methylation profiling. Despite the generally poor prognosis of CUP, a minority of patients can expect to benefit from targeted therapy despite being agnostic to the tissue of origin. Studies have explored the use of various molecular profiling techniques to predict prognostic and therapeutic biomarkers, with the goal of improving outcome for patients with CUP. However, discordant results between non-randomized and randomized clinical trials in evaluating tumor-type specific therapies raise uncertainties of the benefits of molecularly-predicted tissue of origin-based treatment in routine clinical use. Nevertheless, the current overall trend is in favor of using molecular tools to refine the diagnosis and clinical management of patients with CUP. More large-cohort, randomized prospective studies are needed to assess and validate the utility and feasibility of molecular profiling to uncover potentially targetable genetic alterations. These efforts will also yield further biological insights into the biology and pathogenesis of CUP (Graphical Abstract).

A Review on Cancer of Unknown Primary Origin: The Role of Molecular Biomarkers in the Identification of Unknown Primary Origin

The primary site cannot be found after clinical and pathological evaluation, which are called cancers of unknown primary origin (CUP). CUPs may resemble a specific primary tumor site which shares common clinicopathological characteristics and prognosis. However, it may be present as a distinct disease entity with undifferentiated pathological features. More than 4% of patients are diagnosed as CUP. These patients were diagnosed as malignant tumors by cytology or pathology. And they were usually treated with empirical chemotherapy and associated with a poor prognosis. How to accurately diagnose and treat a cancer of unknown primary origin is a major clinical concern. To address this question, a complex assessment is carried out which includes a complete medical history of the patient, physical examination, complete blood count, urinalysis, serum chemistries, histologic evaluation, chest radiograph, computed tomography, magnetic resonance imaging, and immunohistochemistry (IHC) studies. Molecular diagnostic information reflects that CUP's molecular characteristics are similar to primary tumors with the development of genomics and the expansion of gene sequencing technology. Gene expression profiling is the most commonly used molecular diagnostic method for CUP. In this chapter, we summarize the current diagnostic methods and challenges of CUP, and the clinical value of the molecular-level tumor diagnostic technique.

Skeletal Metastases of Unknown Primary: Biological Landscape and Clinical Overview

Skeletal metastases of unknown primary (SMUP) represent a clinical challenge in dealing with patients diagnosed with bone metastases. Management of these patients has improved significantly in the past few years. however, it is fraught with a lack of evidence. While some patients have achieved impressive gains, a more systematic and tailored treatment is required. Nevertheless, in real-life practice, the outlook at the beginning of treatment for SMUP is decidedly somber. An incomplete translational relevance of pathological and clinical data on the mortality and morbidity rate has had unsatisfactory consequences for SMUP patients and their physicians. We examined several approaches to confront the available evidence; three key points emerged. The characterization of the SMUP biological profile is essential to driving clinical decisions by integrating genetic and molecular profiles into a multi-step diagnostic work-up. Nonetheless, a pragmatic investigation plan and therapy of SMUP cannot follow a single template; it must be adapted to different pathophysiological dynamics and coordinated with efforts of a systematic algorithm and high-quality data derived from statistically powered clinical trials. The discussion in this review points out that greater efforts are required to face the unmet needs present in SMUP patients in oncology.

Application of a Neural Network Whole Transcriptome-Based Pan-Cancer Method for Diagnosis of Primary and Metastatic Cancers

IMPORTANCE

A molecular diagnostic method that incorporates information about the transcriptional status of all genes across multiple tissue types can strengthen confidence in cancer diagnosis.

OBJECTIVE

To determine the practical use of a whole transcriptome-based pan-cancer method in diagnosing primary and metastatic cancers and resolving complex diagnoses.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional diagnostic study assessed Supervised Cancer Origin Prediction Using Expression (SCOPE), a machine learning method using whole-transcriptome RNA sequencing data. Training was performed on publicly available primary cancer data sets, including The Cancer Genome Atlas. Testing was performed retrospectively on untreated primary cancers and treated metastases from volunteer adult patients at BC Cancer in Vancouver, British Columbia, from January 1, 2013, to March 31, 2016, and testing spanned 10 822 samples and 66 output classes representing untreated primary cancers (n = 40) and adjacent normal tissues (n = 26). SCOPE's performance was demonstrated on 211 untreated primary mesothelioma cancers and 201 treatment-resistant metastatic cancers. Finally, SCOPE was used to identify the putative site of origin in 15 cases with initial presentation as cancers with unknown primary of origin.

RESULTS

A total of 10 688 adult patient samples representing 40 untreated primary tumor types and 26 adjacent-normal tissues were used for training. Demographic data were not available for all data sets. Among the training data set, 5157 of 10 244 (50.3%) were male and the mean (SD) age was 58.9 (14.5) years. Testing was performed on 211 patients with untreated primary mesothelioma (173 [82.0%] male; mean [SD] age, 64.5 [11.3] years); 201 patients with treatment-resistant cancers (141 [70.1%] female; mean [SD] age, 55.6 [12.9] years); and 15 patients with cancers of unknown primary of origin; among the treatment-resistant cancers, 168 were metastatic, and 33 were the primary presentation. An accuracy rate of 99% was obtained for primary epithelioid mesotheliomas tested (125 of 126). The remaining 85 mesotheliomas had a mixed etiology (sarcomatoid mesotheliomas) and were correctly identified as a mixture of their primary components, with potential implications in resolving subtypes and incidences of mixed histology. SCOPE achieved an overall mean (SD) accuracy rate of 86% (11%) and F1 score of 0.79 (0.12) on the 201 treatment-resistant cancers and matched 12 of 15 of the putative diagnoses for cancers with indeterminate diagnosis from conventional pathology.

CONCLUSIONS AND RELEVANCE

These results suggest that machine learning approaches incorporating multiple tumor profiles can more accurately identify the cancerous state and discriminate it from normal cells. SCOPE uses the whole transcriptomes from normal and tumor tissues, and results of this study suggest that it performs well for rare cancer types, primary cancers, treatment-resistant metastatic cancers, and cancers of unknown primary of origin. Genes most relevant in SCOPE's decision making were examined, and several are known biological markers of respective cancers. SCOPE may be applied as an orthogonal diagnostic method in cases where the site of origin of a cancer is unknown, or when standard pathology assessment is inconclusive.

Evaluation of Carcinoma of Unknown Primary on Cytologic Specimens

Carcinoma of unknown primary is defined as metastatic carcinoma without a clinically obvious primary tumor. Determining the tissue of origin in carcinoma of unknown primary is important for site-directed therapy. Immunohistochemistry is the most widely used tool for the work-up of metastases, but molecular profiling assays are also available. This review provides an overview of immunohistochemical stains in the work-up of metastatic carcinoma, with a focus on newer site-specific markers, and discusses the role of gene expression profiling assays for determining tissue of origin. The utility of cytopathology specimens in the evaluation of carcinoma of unknown primary also is highlighted.

Cancer of unknown primary-Epidemiological trends and relevance of comprehensive genomic profiling

Background

Cancer of unknown primary (CUP) is a distinct clinicopathological entity with poor prognosis, frequently resistant to chemotherapy. Comprehensive genomic profiling (CGP) by next‐generation sequencing potentially identifies novel treatment options for CUP patients. The objective of this study was to determine incidence and survival trends and to discuss the value of CGP in CUP patients.

Methods

Age‐standardized incidence rates (ASR) per 100 000 were calculated for 2935 CUP patients from 1981 to 2014 using cancer registry data of the canton of Zurich, Switzerland. Kaplan–Meier survival curves were estimated for sex, age, and histological groups. Cox proportional hazards regression models were used to estimate adjusted hazard ratios (HR). A literature review was conducted to assess the current use of CGP in CUP patients.

Results

ASR of CUP increased from 10.3 to 17.6 between 1981 and 1997 and decreased to 5.8/100 000 in 2014. Mean overall survival remained stable. Mortality was significantly lower for patients with squamous cell carcinoma (HR 0.48 [95% CI, 0.41‐0.57]) and neuroendocrine carcinoma (0.75 [0.63‐0.88]) and higher for unclassified neoplasms (1.25 [1.13‐1.66]) compared to adenocarcinomas. The literature review identified 10 studies using CGP of CUP tissue. Clinically relevant mutations were identified in up to 85% of CUP patients, of which 13%‐64% may benefit from currently available drugs.

Conclusions

CUP incidence decreased probably due to improved diagnostics, but mortality did not improve over the last 34 years. CGP testing may help to identify molecular signatures in CUP patients and enable targeted treatment.

Omics-based molecular techniques in oral pathology centred cancer: prospect and challenges in Africa

BACKGROUND

The completion of the human genome project and the accomplished milestones in the human proteome project; as well as the progress made so far in computational bioinformatics and "big data" processing have contributed immensely to individualized/personalized medicine in the developed world.

MAIN BODY

At the dawn of precision medicine, various omics-based therapies and bioengineering can now be applied accurately for the diagnosis, prognosis, treatment, and risk stratification of cancer in a manner that was hitherto not thought possible. The widespread introduction of genomics and other omics-based approaches into the postgraduate training curriculum of diverse medical and dental specialties, including pathology has improved the proficiency of practitioners in the use of novel molecular signatures in patient management. In addition, intricate details about disease disparity among different human populations are beginning to emerge. This would facilitate the use of tailor-made novel theranostic methods based on emerging molecular evidences.

CONCLUSION

In this review, we examined the challenges and prospects of using currently available omics-based technologies vis-à-vis oral pathology as well as prompt cancer diagnosis and treatment in a resource limited setting.

Cancer of Unknown Primary origin in the genomic era: Elucidating the dark box of cancer

Cancer of Unknown Primary (CUP) comprises a heterogeneous disease group with diagnosis of metastatic malignancy in the absence of an identifiable primary site after diagnostic work up. CUP may either resemble a specific primary tumor site sharing common clinicopathological characteristics and prognosis, or present as a distinct disease entity with undifferentiated pathological features, usually bearing dismal prognosis. Diagnosis and management have traditionally been based on clinicopathological characteristics and therapeutic strategies have been mainly empirical. In the last decade, the advent of massive gene sequencing and the advances in genomic technologies have shed light on the genomic landscape of CUP. Several gene panel tests are currently commercially available and are used in an effort to correlate the genomic characteristics of a specific CUP tumor to those of a known primary tumor, guiding thus therapeutic management. Nevertheless, these efforts are hampered by the rarity of CUP and the inability to validate the results of such tests due to the paucity of randomized clinical trials. In the current work, we provide an overview of CUP with emphasis on the impact of the genome sequencing technologies on diagnosis and management of these tumors. We also discuss potential implications of genomics for the future treatment of CUP and address the challenges of the implementation of these therapeutic strategies in routine clinical practice.

A phase II study of cisplatin /S-1 in patients with carcinomas of unknown primary site

BACKGROUND

Carcinomas of unknown primary site (CUPs) are heterogeneous tumors associated with a poor prognosis. This phase II trial was designed to evaluate the efficacy and safety of a novel combination chemotherapy of S-1 and cisplatin (CDDP) in patients with CUP.

PATIENTS AND METHODS

Patients with previously untreated CUPs were eligible for this trial. The treatment schedule consisted of oral S-1 (40 mg/m(2)) twice a day on days 1-21, and intravenous CDDP (60 mg/m(2)) on day 8. This schedule was repeated every 5 weeks.

RESULTS

A total of 46 patients were enrolled. The overall response rate and the disease control rate were 41.3% and 80.4%, respectively. The median overall survival time was 17.4 months. Grade 3/4 neutropenia, thrombocytopenia, and febrile neutropenia occurred in 28.3%, 13.0%, and 2.2% of the patients, respectively.

CONCLUSION

CDDP plus S-1 combination chemotherapy is well tolerated and active first-line empiric therapies for patients with CUP.

Molecular profiling diagnosis in unknown primary cancer: accuracy and ability to complement standard pathology

BACKGROUND

Molecular tumor profiling (MTP) is a potentially powerful diagnostic tool for identifying the tissue of origin in patients with cancer of unknown primary (CUP). However, validation of the accuracy and clinical value of MTP has been difficult because the anatomic primary site in most patients is never identified.

METHODS

From March 2008 through January 2010, clinicopathologic data from 171 CUP patients who had MTP (CancerTYPE ID; bioTheranostics, Inc, San Diego, CA) performed on archived material were evaluated. The accuracy of MTP diagnoses was evaluated by comparison with (1) latent primary tumor sites found months/years later; (2) initial single diagnoses by immunohistochemistry (IHC); and (3) additional directed IHC and/or clinicopathologic findings evaluated after MTP diagnoses.

RESULTS

A single MTP diagnosis was made in 144 of 149 patients with adequate tumor specimens. Eighteen of 24 patients with latent primaries discovered months to years later had correct diagnoses by MTP (75%), and these diagnoses compared favorably with IHC. Single IHC diagnoses matched MTP diagnoses in 40 of 52 patients (77%). IHC predictions of 2 or more possible primaries compared poorly with MTP diagnoses. However, additional targeted IHC and clinical/histologic evaluation supported the MTP diagnosis in 26 of 35 patients (74%). Clinical features were usually consistent with MTP diagnoses (70%).

CONCLUSIONS

The diagnostic accuracy of this MTP assay was supported by a high level of agreement with identified latent primaries (75%), single IHC diagnoses (77%), and additional directed IHC and/or clinical/histologic findings (74%) prompted by the MTP diagnoses. MTP complements standard pathologic evaluation in determining the tissue of origin in patients with CUP, particularly when IHC is inconclusive.

Diagnostic work-up of carcinoma of unknown primary: from immunohistochemistry to molecular profiling

Carcinoma of unknown primary (CUP) remains a common and challenging clinical problem. The aim of diagnostic work-up in CUP is to classify as specifically as possible the cancer affecting the patient, according to the broad tumour type, subtype and, where possible, site of origin. This classification currently best predicts patient outcome and guides optimal treatment. a stepwise approach to diagnostic work-up is described. although pathology is based on morphology, the assessment of tissue-specific genes through immunohistochemistry (IHC) substantially helps tumour classification at each diagnostic step. For IHC in CUP, recent improvements include more standardised approaches and marker panels plus new markers. Tissue-specific genes are also being used in CUP work-up through molecular profiling. Large-scale profiles of hundreds of tumours of different types have been generated, compared and used to generate diagnostic algorithms. Commercial tests for CUP classification have been developed at the mRNa and microRNA and (miRNA) levels and validated in metastatic tumours and CUPs. While currently optimal pathology and IHC remain the 'gold standard' for CUP diagnostic work-up, and full clinical correlation is vital, the molecular tests appear to perform well: in the main diagnostic challenge of undifferentiated or poorly differentiated tumours, molecular profiling performs as well as or better than IHC.

Cancer of unknown primary site: improved patient management with molecular and immunohistochemical diagnosis

Cancer of unknown primary site (CUP) is a common heterogeneous clinicopathologic syndrome, but investigations and publications regarding these patients are rare. For the last 20 years, empiric "broad-spectrum" chemotherapy has been the standard therapy for the majority of these patients. More recently, improved immunocytochemistry and advent of gene-expression profiling have provided the diagnostic tools necessary to accurately define the tissue of origin in most patients. Molecular profiling assays complement standard pathologic diagnosis, and a recently reported large prospective study demonstrated an improvement in outcome for patients treated with site-specific therapy directed by the molecular assay diagnoses compared with empiric chemotherapy. Survival in molecularly diagnosed patients was as expected for those particular tumor types. The evaluation of patients has become more standardized. The empiric-chemotherapy era is ending and customized therapies based on accurate tissue of origin diagnoses have arrived. Eventually the recognition of the molecular aberrations responsible for the growth and metastasis of solid tumors, regardless of the tissue of origin, will lead to more precise and effective therapy for patients with advanced cancers.

Gene expression-based diagnostics for molecular cancer classification of difficult to diagnose tumors

INTRODUCTION

Standardized methods for accurate tumor classification are of critical importance for cancer diagnosis and treatment, particularly in diagnostically-challenging cases where site-directed therapies are an option. Molecular diagnostics for tumor classification, subclassification and site of origin determination based on advances in gene expression profiling have translated into clinical practice as complementary approaches to clinicopathological evaluations.

AREAS COVERED

In this review, the foundational science of gene expression-based cancer classification, technical and clinical considerations for clinical translation, and an overview of molecular signatures of tumor classification that are available for clinical use will be discussed. Proposed approaches will also be described for further integration of molecular tests for cancer classification into the diagnostic paradigm using a tissue-based strategy as a key component to direct evaluation.

EXPERT OPINION

Increasing evidence of improved patient outcomes with the application of site and molecularly-targeted cancer therapy through use of molecular tools highlights the growing potential for these gene expression-based diagnostics to positively impact patient management. Looking forward, the availability of adequate tissue will be a significant issue and limiting factor as cancer diagnosis progresses; when the tumor specimen is limited, use of molecular classification may be a reasonable early step in the evaluation, particularly if the tumor is poorly-differentiated and has atypical features.

Papillary Renal Carcinoma Presenting as a Cancer of Unknown Primary (CUP) and Diagnosed through Gene Expression Profiling

Cancer of unknown primary (CUP) is a clinical syndrome representing many types of cancers and diagnoses are typically made after review of clinical presentation, pathology (including immunohistochemical staining) and imaging studies. Treatment with systemic chemotherapy has been shown to result in fairly reproducible objective response rates. Herein, a case of a patient who was initially diagnosed with a poorly differentiated adenocarcinoma of unknown origin is reported. After mRNA gene expression profiling (commercially available CancerTYPE ID), a specific diagnosis of papillary renal cell carcinoma (RCC) was made and then confirmed with additional immunohistochemical staining. The patient was treated with targeted therapy and an objective radiographic response was seen. A literature review suggests this to be the first patient with papillary RCC, identified by molecular profiling, and benefitting from a targeted agent that otherwise would not have been considered in the setting of CUP. This case underscores the importance of considering the use of newer testing technologies in the interest of offering patients more specific, targeted therapy in order to improve efficacy and spare patients toxicities of less specific, empiric chemotherapeutic regimens.

Cancer of unknown primary site

Cancer of unknown primary site (CUP) is a well recognised clinical disorder, accounting for 3-5% of all malignant epithelial tumours. CUP is clinically characterised as an aggressive disease with early dissemination. Diagnostic approaches to identify the primary site include detailed histopathological examination with specific immunohistochemistry and radiological assessment. Gene-profiling microarray diagnosis has high sensitivity, but further prospective study is necessary to establish whether patients' outcomes are improved by its clinical use. Metastatic adenocarcinoma is the most common CUP histopathology (80%). CUP patients are divided into subsets of favourable (20%) and unfavourable (80%) prognosis. Favourable subsets are mostly given locoregional treatment or systemic platinum-based chemotherapy. Responses and survival are similar to those of patients with relevant known primary tumours. Patients in unfavourable subsets are treated with empirical chemotherapy based on combination regimens of platinum or taxane, but responses and survival are generally poor.

A pathway-based approach to identify molecular biomarkers in cancer

Many examples highlight the power of gene expression profiles, or signatures, to provide an understanding of biological phenotypes. This is best seen in the context of cancer, where expression signatures have tremendous power to identify new cancer subtypes and to predict clinical outcomes. Gene expression profiles have been developed to personalize medicine, accurately predicting disease recurrence and tumor response to therapy. The use of these signatures as surrogate phenotypes allows us to link diverse experimental systems, which dissect the complexity of biological systems, with the in vivo setting in a way that was not previously feasible. Taken together, these new genomic tools provide the opportunity to develop rational strategies for treating the individual cancer patient.

Carcinomas of an unknown primary origin--diagnosis and treatment

Carcinomas of an unknown primary origin (CUP) account for 3-5% of all malignancies and are thus among the ten most-frequent cancers worldwide. Having a specific and unique phenotype of early and usually aggressive metastatic dissemination with no identifiable primary tumor, CUP are a challenge for physicians. The diagnostic workup of patients with CUP includes a careful clinical and extensive histopathological examination, as well as the use of imaging techniques. CUP can be divided into favorable and unfavorable subsets. Patients with unfavorable CUP subsets have a poor prognosis with a median survival of approximately 8 months; the optimal chemotherapy regimen for these patients remains to be determined. Although studies have focused on the introduction of new cytotoxic agents with broad-spectrum clinical activity (such as gemcitabine, irinotecan, and taxanes), no randomized trial has provided clear evidence of a survival benefit. Molecular targeted therapies that are approved for other solid tumors are now considered for the treatment of patients with CUP. Molecular diagnostic tools, such as DNA microarray analysis, could help in the search for 'lost' CUP origins. In this Review, we describe the clinical evaluation of patients with CUP, and discuss treatment strategies and outcomes of patients with various CUP subsets.

Cancer of unknown primary site: 20 questions to be answered

Cancer of unknown primary (CUP) is a common, well-recognized and heterogeneous clinical syndrome. Patients with CUP present with metastatic disease in the absence of an identifiable primary tumour despite a diagnostic work-up. Aetiologically, CUP might either harbor primaries that cannot be detected by the standardized diagnostic investigations or carry distinct genetic and epigenetic aberrations. In this article we try to clarify the clinical and pathological enigma of CUP by answering 20 important questions related to this entity.

Gene-expression assays and personalized cancer care: tissue-of-origin test for cancer of unknown primary origin

Cancer of unknown primary (CUP) is one of the ten most frequently diagnosed cancers in developed countries and accounts for 3–5% of all new cancer cases. For all cancer management, chemotherapeutic regimens and targeted agents have increasingly become primary-site dependent over the last decade, and thus, accurate identification of the primary site is crucial for CUP patients. Histopathologic examination along with immunohistochemical studies and different imaging modalities are most often performed for this purpose, but still a significant number of patients remain with an unidentified primary. Recently, gene-expression profiling assays have emerged as alternative tests for tumor tissue of origin determination. It is expected that molecular determination of the origin in patients with CUP will aid in the determination of management strategies. It is thus possible that personalized treatment of CUP patients based on molecular classification could significantly improve patient outcomes.

Cancer of unknown primary: progress in the search for improved and rapid diagnosis leading toward superior patient outcomes

This paper explores the enigma of cancer of unknown primary (CUP) in relation to rapidly improving molecular diagnostic approaches. It is based on the first global collaboration meeting on improving research and clinical outcomes in CUP organized by the CUP Foundation. We review the difficulties of classifying this widely heterogeneous disease and the available diagnostic and pathological evaluative techniques, focusing on molecular profiling. Retrospective studies in CUP patients are shown to provide indirect validation of the accuracy of several platforms of gene expression profiling assays that may identify CUP subsets that respond favorably to active chemotherapy regimens. This review concludes that the recent major improvements in pathologic and molecular diagnostics, coupled with new improved therapies for several specific advanced solid tumors, need to be harmonized with more evidence from clinical-translational trials. All patients with CUP could thus be appropriately managed without the constant uncertainty that has previously severely hampered patient care and optimal outcomes. The longer-term objective is to understand the biology of highly metastatic disease, leading to the development of future global therapeutic programs. Current clinical studies, such as CUP-ONE, will address some of these issues.

Unknown primary tumors

An unknown primary tumor (UPT) is defined by the presence of a metastatic cancer without a known primary site of origin despite a standardized diagnostic workup. Clinically, UPTs show rapid progression and early dissemination, with signs and symptoms related to the metastatic site. The molecular bases of their biology remain largely unknown, with no evidence as to whether they represent a distinct biological entity. Immunohistochemistry remain the best diagnostic tool in term of cost-effectiveness, but the time-consuming "algorithmic process" it relies on has led to the application of new molecular techniques for the identification of the primary site of UPTs. For example, several microarray or miRNA classifications of UPTs have been used, with an accuracy in the prediction of the primary site as high as 90%. It should be noted that validating a prediction of tissue origin is challenging in these patients, since most of them will never have a primary site identified. Moreover, prospective studies to determine whether selection of treatment options based on such profiling methods actually improves patient outcome are still missing. In the last few years functional imaging (i.e. FDG-PET/CT) has gained a main role in the detection of the site of origin of UPTs and is currently recommended by the European Association of Nuclear Medicine. However, despite recent refinements in the diagnostic workup, the site of origin of UPT often remains elusive. As a consequence, treatment of patients with UPT is still empirical and inadequate.

Accurate classification of metastatic brain tumors using a novel microRNA-based test

BACKGROUND

Identification of the tissue of origin of a brain metastatic tumor is vital to its management. Carcinoma of unknown primary (CUP) is common in oncology, representing 3%-5% of all invasive malignancies. We aimed to validate a recently developed microRNA-based quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) test for identifying the tumor tissue of origin, first in a consecutive cohort of metastatic tumors of known origin and then in a cohort of CUP cases resected from the central nervous system (CNS).

PATIENTS AND METHODS

One hundred two resected CNS metastatic tumors with known origin, previously classified based on the patient's clinical history and pathological data, as well as a second cohort of resected CNS tumors from 57 patients originally diagnosed as CUP were studied. A qRT-PCR diagnostic assay that measures the expression level of 48 microRNAs was used to classify the tissue of origin of these metastatic tumors.

RESULTS

In this blinded study, the test predictions correctly identified the reference diagnosis of the samples of known origin, excluding samples from prostate origin, in 84% of cases. In the second CUP patient cohort, the test prediction was in agreement with the diagnosis that was later confirmed clinically or with pathological evaluation in 80% of cases.

CONCLUSION

In a cohort of brain and spinal metastases, a previously developed test based on the expression of 48 microRNAs allowed accurate identification of the tumor tissue of origin in the majority of cases. The high accuracy of this test in identifying the tissue of origin of metastases of unknown primary is demonstrated for the first time and may have broad clinical application.

Emerging techniques for determining the tissue of origin in patients with unknown primary carcinoma

New molecular tests to assign a putative tissue of origin in patients with carcinoma of unknown primary (CUP) have recently become commercially available. This editorial addresses this new technology in terms of our current understanding of CUP, and how these tests may affect its management.

Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

Identification of the tissue of origin of a tumor is vital to its management. Previous studies showed tissue-specific expression patterns of microRNA and suggested that microRNA profiling would be useful in addressing this diagnostic challenge. MicroRNAs are well preserved in formalin-fixed, paraffin-embedded (FFPE) samples, further supporting this approach. To develop a standardized assay for identification of the tissue origin of FFPE tumor samples, we used microarray data from 504 tumor samples to select a shortlist of 104 microRNA biomarker candidates. These 104 microRNAs were profiled by proprietary quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) on 356 FFPE tumor samples. A total of 48 microRNAs were chosen from this list of candidates and used to train a classifier. We developed a clinical test for the identification of the tumor tissue of origin based on a standardized protocol and defined the classification criteria. The test measures expression levels of 48 microRNAs by qRT-PCR, and predicts the tissue of origin among 25 possible classes, corresponding to 17 distinct tissues and organs. The biologically motivated classifier combines the predictions generated by a binary decision tree and K-nearest neighbors (KNN). The classifier was validated on an independent, blinded set of 204 FFPE tumor samples, including nearly 100 metastatic tumor samples. The test predictions correctly identified the reference diagnosis in 85% of the cases. In 66% of the cases the two algorithm predictions (tree and KNN) agreed on a single-tissue origin, which was identical to the reference diagnosis in 90% of cases. Thus, a qRT-PCR test based on the expression profile of 48 tissue-specific microRNAs allows accurate identification of the tumor tissue of origin.

Molecular classification of cancers of unknown primary site

Cancer of unknown primary site is a common metastatic cancer, diagnosed in about 50 000 patients per year in the US. The diagnosis, classification, and management of patients with carcinoma of unknown primary site has been difficult and frustrating. The therapy has usually been empiric for the majority of patients, and their prognosis has been poor. Molecular classification of metastatic cancers with known primary sites has been accurate (76-89%), as reported from several studies. Molecular profiling of initial biopsy specimens has tremendous potential as a test to diagnose the site of tumor origin in patients with unknown primary cancer. Several retrospective studies of molecular profiling assays have provided indirect validation of the accuracy of primary site prediction, based on correlations with clinicopathologic features. One additional study of initial diagnostic biopsies in unknown primary cancer patients, where primary tumor sites were identified months to years later, has provided more direct validation of the accuracy of molecular classification (the primary tumor sites of 15 of 20 patients were correctly predicted). The ability to diagnose and classify unknown primary cancer more precisely would allow for more site-specific or targeted therapy, and likely improve patient outcomes. Several clinical studies are in progress or planned to test this concept.

The pathophysiology, diagnosis and prognosis of adrenocortical tumors revisited by transcriptome analyses

Analyzing gene expression (transcriptome) in tissue is now reliable using industrial pangenomic microarrays. Accumulating data on adrenal cortex and adrenocortical tumor transcriptomes have already identified striking transcriptome differences not only between adenoma and carcinoma but also between two sets of carcinoma, which have very different prognoses. These findings result in the development of diagnostic and prognostic molecular predictors, which improve the outcome determination compared with standard clinical and pathological tools. These transcriptome data observing adrenocortical tumor phenotype in great but complex detail, combined with genomic and proteomic information, will function for future research investigating the pathophysiology of their tumorigenesis and hormonal secretion.

Molecular profiling in unknown primary cancer: accuracy of tissue of origin prediction

INTRODUCTION

This retrospective, multi-institutional study evaluated the accuracy of tissue-of-origin prediction by molecular profiling in patients with carcinoma of unknown primary site (CUP).

METHODS

Thirty-eight of 501 patients (7.6%) with CUP, seen in 2000-2008, had their latent primary site tumor subsequently identified during life. Twenty-eight of these patients (73.7%) had adequate initial tissue biopsies available for molecular profiling with a reverse transcriptase-polymerase chain reaction (RT-PCR) assay (Cancer Type ID; bioTheranostics, Inc., San Diego, CA). The assay was performed on formalin-fixed paraffin-embedded biopsy specimens in a blinded fashion, and the assay results were compared with clinicopathologic data and the actual latent primary sites.

RESULTS

Twenty of the 28 (71.4%) RT-PCR assays were successfully completed (eight biopsies had either insufficient tumor or poorly preserved RNA). Fifteen of the 20 assay predictions (75%) were correct (95% confidence interval, 60%-85%), corresponding to the actual latent primary sites identified after the initial diagnosis of CUP. Primary sites correctly identified included breast (four patients), ovary/primary peritoneal (four patients), non-small cell lung (three patients), colorectal (two patients), gastric (one patient), and melanoma (one patient). Three predictions were incorrect (intestinal, testicular, sarcoma) in patients with gastroesophageal, pancreatic, and non-small cell lung cancer, respectively, and two were unclassifiable in patients with non-small cell lung cancer. Clinicopathologic findings were helpful in suggesting the correct primary site in some patients and appear to complement the molecular assay findings.

CONCLUSIONS

These data validate the reliability of this assay in predicting the primary site in CUP patients and may form the basis for more successful site-directed therapy, when used in concert with clinicopathologic data.

A taxonomy of epithelial human cancer and their metastases

Background

Microarray technology has allowed to molecularly characterize many different cancer sites. This technology has the potential to individualize therapy and to discover new drug targets. However, due to technological differences and issues in standardized sample collection no study has evaluated the molecular profile of epithelial human cancer in a large number of samples and tissues. Additionally, it has not yet been extensively investigated whether metastases resemble their tissue of origin or tissue of destination.

Methods

We studied the expression profiles of a series of 1566 primary and 178 metastases by unsupervised hierarchical clustering. The clustering profile was subsequently investigated and correlated with clinico-pathological data. Statistical enrichment of clinico-pathological annotations of groups of samples was investigated using Fisher exact test. Gene set enrichment analysis (GSEA) and DAVID functional enrichment analysis were used to investigate the molecular pathways. Kaplan-Meier survival analysis and log-rank tests were used to investigate prognostic significance of gene signatures.

Results

Large clusters corresponding to breast, gastrointestinal, ovarian and kidney primary tissues emerged from the data. Chromophobe renal cell carcinoma clustered together with follicular differentiated thyroid carcinoma, which supports recent morphological descriptions of thyroid follicular carcinoma-like tumors in the kidney and suggests that they represent a subtype of chromophobe carcinoma. We also found an expression signature identifying primary tumors of squamous cell histology in multiple tissues. Next, a subset of ovarian tumors enriched with endometrioid histology clustered together with endometrium tumors, confirming that they share their etiopathogenesis, which strongly differs from serous ovarian tumors. In addition, the clustering of colon and breast tumors correlated with clinico-pathological characteristics. Moreover, a signature was developed based on our unsupervised clustering of breast tumors and this was predictive for disease-specific survival in three independent studies. Next, the metastases from ovarian, breast, lung and vulva cluster with their tissue of origin while metastases from colon showed a bimodal distribution. A significant part clusters with tissue of origin while the remaining tumors cluster with the tissue of destination.

Conclusion

Our molecular taxonomy of epithelial human cancer indicates surprising correlations over tissues. This may have a significant impact on the classification of many cancer sites and may guide pathologists, both in research and daily practice. Moreover, these results based on unsupervised analysis yielded a signature predictive of clinical outcome in breast cancer. Additionally, we hypothesize that metastases from gastrointestinal origin either remember their tissue of origin or adapt to the tissue of destination. More specifically, colon metastases in the liver show strong evidence for such a bimodal tissue specific profile.

Gene expression profiling: decoding breast cancer

Gene expression assays that are used in daily clinical practice for treating early breast cancer patients have been introduced in the clinic only recently. This review discusses the development of these arrays, summarizes the validation of those that are commercially available and indicates how the information provided by these assays can help in the care of patients. The review also provides an extensive overview of commercially available assays focusing on MammaPrint, the first and only assay for breast cancer management that has been cleared by the FDA.