Identification of tissue of origin in body fluid specimens using a gene expression microarray assay

Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type

•

CUP occurs in as many as 3–5% of patients when standard diagnostic tests are not able to determine the origin of cancer.

•

MI GPSai (Genomic Prevalence Score) is an AI that uses genomic and transcriptomic data to elucidate tumor origin.

•

The algorithm was trained on molecular data from 57,489 cases and validated on 19,555 cases.

•

MI GPSai predicted the tumor type out of 21 options in the labeled data set with an accuracy of over 94% on 93% of cases.

•

When also considering the second highest prediction, the accuracy increases to 97%.

Cancer of Unknown Primary (CUP) occurs in 3–5% of patients when standard histological diagnostic tests are unable to determine the origin of metastatic cancer. Typically, a CUP diagnosis is treated empirically and has very poor outcomes, with median overall survival less than one year. Gene expression profiling alone has been used to identify the tissue of origin but struggles with low neoplastic percentage in metastatic sites which is where identification is often most needed. MI GPSai, a Genomic Prevalence Score, uses DNA sequencing and whole transcriptome data coupled with machine learning to aid in the diagnosis of cancer. The algorithm trained on genomic data from 34,352 cases and genomic and transcriptomic data from 23,137 cases and was validated on 19,555 cases. MI GPSai predicted the tumor type in the labeled data set with an accuracy of over 94% on 93% of cases while deliberating amongst 21 possible categories of cancer. When also considering the second highest prediction, the accuracy increases to 97%. Additionally, MI GPSai rendered a prediction for 71.7% of CUP cases. Pathologist evaluation of discrepancies between submitted diagnosis and MI GPSai predictions resulted in change of diagnosis in 41.3% of the time. MI GPSai provides clinically meaningful information in a large proportion of CUP cases and inclusion of MI GPSai in clinical routine could improve diagnostic fidelity. Moreover, all genomic markers essential for therapy selection are assessed in this assay, maximizing the clinical utility for patients within a single test.

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.

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.

Molecular classification of cancer with the 92-gene assay in cytology and limited tissue samples

BACKGROUND

Detailed molecular evaluation of cytology and limited tissue samples is increasingly becoming the standard for cancer care. Reproducible and accurate diagnostic approaches with reduced demands on cellularity are an ongoing unmet need. This study evaluated the performance of a 92-gene assay for molecular diagnosis of tumor type/subtype in cytology and limited tissue samples.

METHODS

Clinical validation of accuracy for the 92-gene assay in limited tissue samples such as cytology cell blocks, core biopsies and small excisions was conducted in a blinded multi-institutional study (N = 109, 48% metastatic, 53% grade II and III). Analytical success rate and diagnostic utility were evaluated in a consecutive series of 644 cytology cases submitted for clinical testing.

RESULTS

The 92-gene assay demonstrated 91% sensitivity (95% CI [0.84, 0.95]) for tumor classification, with high accuracy maintained irrespective of specimen type (100%, 92%, and 86% in FNA/cytology cell blocks, core biopsies, and small excisions, respectively; p = 0.26). The assay performed equally well for metastatic versus primary tumors (90% vs 93%, p = 0.73), and across histologic grades (100%, 90%, 89%, in grades I, II, and III, respectively; p = 0.75). In the clinical case series, a molecular diagnosis was reported in 87% of the 644 samples, identifying 23 different tumor types and allowing for additional mutational analysis in selected cases.

CONCLUSIONS

These findings demonstrate high accuracy and analytical success rate of the 92-gene assay, supporting its utility in the molecular diagnosis of cancer for specimens with limited tissue.

Early Detection of Cancer in Blood Using Single-Cell Analysis: A Proposal

Here, we explore the potential of single-cell genomic analysis in blood for early detection of cancer; we consider a method that screens the presence of recurrent patterns of copy number (CN) alterations using sparse single-cell sequencing. We argue for feasibility, based on in silico analysis of existing single-cell data and cancer CN profiles. Sampling procedures from existing diploid single cells can render data for a cell with any given profile. Sampling from multiple published tumor profiles can interrogate cancer clonality via an algorithm that tests the multiplicity of close pairwise similarities among single-cell cancer genomes. The majority of common solid cancers would be detectable in this manner. As any early detection method must be verifiable and actionable, we describe how further analysis of suspect cells can aid in determining risk and anatomic origin. Future affordability rests on currently available procedures for tumor cell enrichment and inexpensive methods for single-cell analysis.

Metastatic Tumors of Unknown Origin: Ancillary Testing in Cytologic Specimens

The application of ancillary studies, such as immunostains, to cytopathology has improved the ability to make accurate diagnoses with precise subclassification. Even with these techniques, there are still aspiration and exfoliative cytology cases for which it remains difficult to definitively determine the source and/or subtype. This article focuses on the well-established and novel ancillary studies used in the modern era of cancer diagnoses in cytopathology, particularly in the diagnostic work-up of metastatic tumors without a known primary.

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.

Actin-based biomechanical features of suspended normal and cancer cells

The mechanical features of individual cells have been regarded as unique indicators of their states, which could constantly change in accordance with cellular events and diseases. Particularly, cancer progression was characterized by the disruption and/or reorganization of actin filaments causing mechanical changes. Thus, mechanical characterization of cells could become an effective cytotechnological approach for early detection of cancer. To develop mechanical cytotechnology, it would be necessary to clarify the mechanical properties in various cell adhesion states. In this study, we investigated the surface mechanical behavior of cancer and normal cells in the adherent and suspended states using atomic force microscopy. Adherent normal stromal cells showed high surface stiffness due to developed actin cap structures on their apical surface, whereas cancer cells did not have developed filamentous actin structures, and their surface stiffness was low. Upon cell detachment from the substrate, filamentous actin structures of adherent normal stromal cells reorganized to the cortical region and their surface stiffness decreased consequently however, the stiffness of suspended normal cells remained higher than that of cancer cells. These suspended state actin structures were similar, regardless of the cell type. Furthermore, the mechanical responses of the cancer and normal stromal cells to perturbation of the actin cytoskeleton were different, suggesting distinct regulatory mechanisms for actin cytoskeleton in cancer and normal cells in both adherent and suspended states. Therefore, cancer cells possess specific mechanical and actin cytoskeleton features different from normal stromal cells.

Massive ascites as the initial manifestation of mantle cell lymphoma: a challenge for the gastroenterologist

Involvement of the serosa may be the presenting feature in a wide and complex variety of lymphoproliferative diseases, with differing clinical outcomes covering a spectrum of benign and malignant conditions. Effusions involving peritoneal and pericardial cavities are uncommon during the course of hematological malignancies. Obstructive and/or infiltrative tumor mass or vascular leakage due to stimulation by vascular endothelial growth factor contribute to the pathogenesis. In addition to clinical findings, cytomorphology and flow cytometric immunophenotyping of the serosal fluid yield valuable information in the differential diagnosis of lymphocytic infiltrates. Herein, we describe the case of primary mantle cell lymphoma in a 75-year-old man presenting with abdominal fullness and weight loss, suggesting a gastrointestinal pathology.

Multisite validation study to determine performance characteristics of a 92-gene molecular cancer classifier

PURPOSE

Accurate tumor classification is essential for cancer management as patient outcomes improve with use of site- and subtype-specific therapies. Current clinicopathologic evaluation is varied in approach, yet standardized diagnoses are critical for determining therapy. While gene expression-based cancer classifiers may potentially meet this need, imperative to determining their application to patient care is validation in rigorously designed studies. Here, we examined the performance of a 92-gene molecular classifier in a large multi-institution cohort.

EXPERIMENTAL DESIGN

Case selection incorporated specimens from more than 50 subtypes, including a range of tumor grades, metastatic and primary tumors, and limited tissue samples. Formalin-fixed, paraffin-embedded tumors passed pathologist-adjudicated review between three institutions. Tumor classification using a 92-gene quantitative reverse transcriptase polymerase chain reaction (RT-PCR) assay was conducted on blinded tumor sections from 790 cases and compared with adjudicated diagnoses.

RESULTS

The 92-gene assay showed overall sensitivities of 87% for tumor type [95% confidence interval (CI), 84-89] and 82% for subtype (95% CI, 79-85). Analyses of metastatic tumors, high-grade tumors, or cases with limited tissue showed no decrease in comparative performance (P = 0.16, 0.58, and 0.16). High specificity (96%-100%) was showed for ruling in a primary tumor in organs commonly harboring metastases. The assay incorrectly excluded the adjudicated diagnosis in 5% of cases.

CONCLUSIONS

The 92-gene assay showed strong performance for accurate molecular classification of a diverse set of tumor histologies. Results support potential use of the assay as a standardized molecular adjunct to routine clinicopathologic evaluation for tumor classification and primary site diagnosis.

Cancers of unknown primary origin: current perspectives and future therapeutic strategies

It is widely accepted that systemic neoplastic spread is a late event in tumour progression. However, sometimes, rapidly invasive cancers are diagnosed because of appearance of metastatic lesions in absence of a clearly detectable primary mass. This kind of disease is referred to as cancer of unknown primary (CUP) origin and accounts for 3-5% of all cancer diagnosis. There is poor consensus on the extent of diagnostic and pathologic evaluations required for these enigmatic cases which still lack effective treatment. Although technology to predict the primary tumour site of origin is improving rapidly, the key issue is concerning the biology which drives early occult metastatic spreading. This review provides the state of the art about clinical and therapeutic management of this malignant syndrome; main interest is addressed to the most recent improvements in CUP molecular biology and pathology, which will lead to successful tailored therapeutic options.