Evaluation of a gene expression microarray-based assay to determine tissue type of origin on a diverse set of 49 malignancies

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).

Massively-parallel sequencing assists the diagnosis and guided treatment of cancers of unknown primary

The clinical management of patients with cancer of unknown primary (CUP) is hampered by the absence of a definitive site of origin. We explored the utility of massively-parallel (next-generation) sequencing for the diagnosis of a primary site of origin and for the identification of novel treatment options. DNA enrichment by hybridization capture of 701 genes of clinical and/or biological importance, followed by massively-parallel sequencing, was performed on 16 CUP patients who had defied attempts to identify a likely site of origin. We obtained high quality data from both fresh-frozen and formalin-fixed, paraffin-embedded samples, demonstrating accessibility to routine diagnostic material. DNA copy-number obtained by massively-parallel sequencing was comparable to that obtained using oligonucleotide microarrays or quantitatively hybridized fluorescently tagged oligonucleotides. Sequencing to an average depth of 458-fold enabled detection of somatically acquired single nucleotide mutations, insertions, deletions and copy-number changes, and measurement of allelic frequency. Common cancer-causing mutations were found in all cancers. Mutation profiling revealed therapeutic gene targets and pathways in 12/16 cases, providing novel treatment options. The presence of driver mutations that are enriched in certain known tumour types, together with mutational signatures indicative of exposure to sunlight or smoking, added to clinical, pathological, and molecular indicators of likely tissue of origin. Massively-parallel DNA sequencing can therefore provide comprehensive mutation, DNA copy-number, and mutational signature data that are of significant clinical value for a majority of CUP patients, providing both cumulative evidence for the diagnosis of primary site and options for future treatment.

A multicenter study directly comparing the diagnostic accuracy of gene expression profiling and immunohistochemistry for primary site identification in metastatic tumors

Metastatic tumors with an uncertain primary site can be a difficult clinical problem. In tens of thousands of patients every year, no confident diagnosis is ever issued, making standard-of-care treatment impossible. Gene expression profiling (GEP) tests currently available to analyze these difficult-to-diagnose tumors have never been directly compared with the diagnostic standard of care, immunochemistry (IHC). This prospectively conducted, blinded, multicenter study compares the diagnostic accuracy of GEP with IHC in identifying the primary site of 157 formalin-fixed paraffin-embedded specimens from metastatic tumors with known primaries, representing the 15 tissues on the GEP test panel. Four pathologists rendered diagnoses by selecting from 84 stains in 2 rounds. GEP was performed using the Pathwork Tissue of Origin Test. Overall, GEP accurately identified 89% of specimens, compared with 83% accuracy using IHC (P=0.013). In the subset of 33 poorly differentiated and undifferentiated carcinomas, GEP accuracy exceeded that of IHC (91% to 71%, P=0.023). In specimens for which pathologists rendered their final diagnosis with a single round of stains, both IHC and GEP exceeded 90% accuracy. However, when the diagnosis required a second round, IHC significantly underperformed GEP (67% to 83%, P<0.001). GEP has been validated as accurate in diagnosing the primary site in metastatic tumors. The Pathwork Tissue of Origin Test used in this study was significantly more accurate than IHC when used to identify the primary site, with the most pronounced superiority observed in specimens that required a second round of stains and in poorly differentiated and undifferentiated metastatic carcinomas.

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.

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.