Prospective gene signature study using microRNA to identify the tissue of origin in patients with carcinoma of unknown primary

The evolution of molecular management of carcinoma of unknown primary

PURPOSE OF REVIEW

There is significant need to improve diagnostic and therapeutic options for patients with cancer of unknown primary (CUP). In this review, we discuss the evolving landscape of molecular profiling in CUP.

RECENT FINDINGS

Molecular profiling is becoming accepted into the diagnostic work-up of CUP patients with tumour mutation profiling now described in international CUP guidelines. Although tissue-of-origin (ToO) molecular tests utilising gene-expression and DNA methylation have existed some time, their clinical benefit remains unclear. Novel technologies utilising whole genome sequencing and machine learning algorithms are showing promise in determining ToO, however further research is required prior to clinical application. A recent international clinical trial found patients treated with molecularly-guided therapy based on comprehensive-panel DNA sequencing had improved progression-free survival compared to chemotherapy alone, confirming utility of performing genomic profiling early in the patient journey. Small phase 2 trials have demonstrated that some CUP patients are responsive to immunotherapy, but the best way to select patients for treatment is not clear.

SUMMARY

Management of CUP requires a multifaceted approach incorporating clinical, histopathological, radiological and molecular sequencing results to assist with identifying the likely ToO and clinically actionable genomic alternations. Rapidly identifying a subset of CUP patients who are likely to benefit from site specific therapy, targeted therapy and/or immunotherapy will improve patient outcomes.

Deep Learning-Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation

BACKGROUND

Carcinoma of unknown primary (CUP) is a subset of metastatic cancers in which the primary tissue source of the cancer cells remains unidentified. CUP is the eighth most common malignancy worldwide, accounting for up to 5% of all malignancies. Representing an exceptionally aggressive metastatic cancer, the median survival is approximately 3 to 6 months. The tissue in which cancer arises plays a key role in our understanding of sensitivities to various forms of cell death. Thus, the lack of knowledge on the tissue of origin (TOO) makes it difficult to devise tailored and effective treatments for patients with CUP. Developing quick and clinically implementable methods to identify the TOO of the primary site is crucial in treating patients with CUP. Noncoding RNAs may hold potential for origin identification and provide a robust route to clinical implementation due to their resistance against chemical degradation.

OBJECTIVE

This study aims to investigate the potential of microRNAs, a subset of noncoding RNAs, as highly accurate biomarkers for detecting the TOO through data-driven, machine learning approaches for metastatic cancers.

METHODS

We used microRNA expression data from The Cancer Genome Atlas data set and assessed various machine learning approaches, from simple classifiers to deep learning approaches. As a test of our classifiers, we evaluated the accuracy on a separate set of 194 primary tumor samples from the Sequence Read Archive. We used permutation feature importance to determine the potential microRNA biomarkers and assessed them with principal component analysis and t-distributed stochastic neighbor embedding visualizations.

RESULTS

Our results show that it is possible to design robust classifiers to detect the TOO for metastatic samples on The Cancer Genome Atlas data set, with an accuracy of up to 97% (351/362), which may be used in situations of CUP. Our findings show that deep learning techniques enhance prediction accuracy. We progressed from an initial accuracy prediction of 62.5% (226/362) with decision trees to 93.2% (337/362) with logistic regression, finally achieving 97% (351/362) accuracy using deep learning on metastatic samples. On the Sequence Read Archive validation set, a lower accuracy of 41.2% (77/188) was achieved by the decision tree, while deep learning achieved a higher accuracy of 80.4% (151/188). Notably, our feature importance analysis showed the top 3 most important features for predicting TOO to be microRNA-10b, microRNA-205, and microRNA-196b, which aligns with previous work.

CONCLUSIONS

Our findings highlight the potential of using machine learning techniques to devise accurate tests for detecting TOO for CUP. Since microRNAs are carried throughout the body via extracellular vesicles secreted from cells, they may serve as key biomarkers for liquid biopsy due to their presence in blood plasma. Our work serves as a foundation toward developing blood-based cancer detection tests based on the presence of microRNA.

Comparison of the classifiers based on mRNA, microRNA and lncRNA expression and DNA methylation profiles for the tumor origin detection

Background

Tumor tissue origin detection is of great importance in determining the appropriate course of treatment for cancer patients. Classifiers based on gene expression and DNA methylation profiles have been confirmed to be feasible and reliable to predict the tumor primary. However, few works have been performed to compare the performance of these classifiers based on different profiles.

Methods

Using gene expression and DNA methylation profiles from The Cancer Genome Atlas (TCGA) project, eight machine learning methods were employed for the tumor tissue origin detection. We then evaluated the predictive performance using DNA methylation, mRNA, microRNA (miRNA) and long non-coding RNA (lncRNA) expression profiles in a comparative manner. A statistical method was introduced to select the most informative CpG sites.

Results

We found that LASSO is the most predictive models based on various profiles. Further analyses indicated that the results derived from DNA methylation (overall accuracy: 97.77%) are better than those derived from mRNA expression (overall accuracy: 88.01%), microRNA expression (overall accuracy: 91.03%) and lncRNA expression (overall accuracy: 95.7%). It has been suggested that we can achieve an overall accuracy >90% using only 1,000 methylated CpG sites for prediction.

Conclusion

In this work, we comprehensively evaluated the performance of classifiers based on different profiles for the tumor origin detection. Our findings demonstrated the effectiveness of DNA methylation as biomarker for tracing tumor tissue origin using LASSO and neural network.

Rare axillary cancer of unknown primary originating from the breast of a 64‑year‑old male patient: A case report and literature review

Cancers of unknown primary (CUPs) are a heterogeneous group of tumors characterized by a difficult diagnosis. The primitive tumor remains unknown, whereas metastases are the most common manifestation. Occult male breast cancers are very rare types of CUPs. The present study describes the case of a 64-year-old man affected by a CUP of presumed mammary origin. The aim of the article and the present review was to focus on their management. To the best of our knowledge, only thirteen cases have been reported in the literature. Because no specific guidelines are available, various approaches have been applied, influencing the treatment and the prognosis of patients with CUP.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3-9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the beta value-based linear support vector (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).

Validation of a Transcriptome-Based Assay for Classifying Cancers of Unknown Primary Origin

INTRODUCTION

Cancers assume a variety of distinct histologies, and may originate from a myriad of sites including solid organs, hematopoietic cells, and connective tissue. Clinical decision-making based on consensus guidelines such as the National Comprehensive Cancer Network (NCCN) is often predicated on a specific histologic and anatomic diagnosis, supported by clinical features and pathologist interpretation of morphology and immunohistochemical (IHC) staining patterns. However, in patients with nonspecific morphologic and IHC findings-in addition to ambiguous clinical presentations such as recurrence versus new primary-a definitive diagnosis may not be possible, resulting in the patient being categorized as having a cancer of unknown primary (CUP). Therapeutic options and clinical outcomes are poor for patients with CUP, with a median survival of 8-11 months.

METHODS

Here, we describe and validate the Tempus Tumor Origin (Tempus TO) assay, an RNA-sequencing-based machine learning classifier capable of discriminating between 68 clinically relevant cancer subtypes. Model accuracy was assessed using primary and/or metastatic samples with known subtype.

RESULTS

We show that the Tempus TO model is 91% accurate when assessed on both a retrospectively held out cohort and a set of samples sequenced after model freeze that collectively contained 9210 total samples with known diagnoses. When evaluated on a cohort of CUPs, the model recapitulated established associations between genomic alterations and cancer subtype.

DISCUSSION

Combining diagnostic prediction tests (e.g., Tempus TO) with sequencing-based variant reporting (e.g., Tempus xT) may expand therapeutic options for patients with cancers of unknown primary or uncertain histology.

Spatial Proteomics for the Molecular Characterization of Breast Cancer

Breast cancer (BC) is a major global health issue, affecting a significant proportion of the female population and contributing to high rates of mortality. One of the primary challenges in the treatment of BC is the disease's heterogeneity, which can lead to ineffective therapies and poor patient outcomes. Spatial proteomics, which involves the study of protein localization within cells, offers a promising approach for understanding the biological processes that contribute to cellular heterogeneity within BC tissue. To fully leverage the potential of spatial proteomics, it is critical to identify early diagnostic biomarkers and therapeutic targets, and to understand protein expression levels and modifications. The subcellular localization of proteins is a key factor in their physiological function, making the study of subcellular localization a major challenge in cell biology. Achieving high resolution at the cellular and subcellular level is essential for obtaining an accurate spatial distribution of proteins, which in turn can enable the application of proteomics in clinical research. In this review, we present a comparison of current methods of spatial proteomics in BC, including untargeted and targeted strategies. Untargeted strategies enable the detection and analysis of proteins and peptides without a predetermined molecular focus, whereas targeted strategies allow the investigation of a predefined set of proteins or peptides of interest, overcoming the limitations associated with the stochastic nature of untargeted proteomics. By directly comparing these methods, we aim to provide insights into their strengths and limitations and their potential applications in BC research.

Cancer of unknown primary site in the mandibular region: A case report

The diagnosis and treatment of cancer of unknown primary site (CUP) present with difficulties and produce a poor prognosis. The current study presents the case of a patient with CUP in the mandibular region was treated with docetaxel and lobaplatin chemotherapy, and vascular embolization of the tumor. The tumor size was markedly reduced and the patient's quality of life improved following radiotherapy. The present case report is accompanied by a discussion of the literature to contextualize the treatment regimen for patients with CUP. These findings will support current treatment practices, inform oncologists and benefit patients with cancer.

From Biology to Diagnosis and Treatment: The Ariadne’s Thread in Cancer of Unknown Primary

Cancer of unknown primary (CUP) encloses a group of heterogeneous tumours, the primary sites for which cannot be identified at the time of diagnosis, despite extensive investigations. CUP has always posed major challenges both in its diagnosis and management, leading to the hypothesis that it is rather a distinct entity with specific genetic and phenotypic aberrations, considering the regression or dormancy of the primary tumour; the development of early, uncommon systemic metastases; and the resistance to therapy. Patients with CUP account for 1–3% of all human malignancies and can be categorised into two prognostic subsets according to their clinicopathologic characteristics at presentation. The diagnosis of CUP mainly depends on the standard evaluation comprising a thorough medical history; complete physical examination; histopathologic morphology and algorithmic immunohistochemistry assessment; and CT scan of the chest, abdomen, and pelvis. However, physicians and patients do not fare well with these criteria and often perform additional time-consuming evaluations to identify the primary tumour site to guide treatment decisions. The development of molecularly guided diagnostic strategies has emerged to complement traditional procedures but has been disappointing thus far. In this review, we present the latest data on CUP regarding the biology, molecular profiling, classification, diagnostic workup, and treatment.

Identification of tissue of origin in cancer of unknown primary using a targeted bisulfite sequencing panel

Aim: To construct a targeted bisulfite sequencing panel predicting origin of cancer of unknown primary. Methods: A bisulfite sequencing panel targeting 2793 tissue-specific markers was performed in 100 clinical samples. Results: The authors' prediction model showed 0.85 accuracy for the 'first-ranked' tissue type and 0.93 accuracy for the 'second-ranked' tissue type using 2793 tissue-specific markers and 0.84 accuracy for the 'first-ranked' tissue type and 0.92 accuracy for the 'second-ranked' tissue type when the number of tissue-specific markers was reduced to 514. Conclusion: Targeted bisulfite sequencing is a useful method for predicting the tissue of origin in patients with cancer of unknown primary.

Molecular Pathology of Lung Cancer

This overview of the molecular pathology of lung cancer includes a review of the most salient molecular alterations of the genome, transcriptome, and the epigenome. The insights provided by the growing use of next-generation sequencing (NGS) in lung cancer will be discussed, and interrelated concepts such as intertumor heterogeneity, intratumor heterogeneity, tumor mutational burden, and the advent of liquid biopsy will be explored. Moreover, this work describes how the evolving field of molecular pathology refines the understanding of different histologic phenotypes of non-small-cell lung cancer (NSCLC) and the underlying biology of small-cell lung cancer. This review will provide an appreciation for how ongoing scientific findings and technologic advances in molecular pathology are crucial for development of biomarkers, therapeutic agents, clinical trials, and ultimately improved patient care.

MicroRNA expression profiling with a droplet digital PCR assay enables molecular diagnosis and prognosis of cancers of unknown primary

Metastasis is responsible for the majority of cancer‐related deaths. Particularly, challenging is the management of metastatic cancer of unknown primary site (CUP), whose tissue of origin (TOO) remains undetermined even after extensive investigations and whose therapy is rather unspecific and poorly effective. Molecular approaches to identify the most probable TOO of CUPs can overcome some of these issues. In this study, we applied a predetermined set of 89 microRNAs (miRNAs) to infer the TOO of 53 metastatic cancers of unknown or uncertain origin. The miRNA expression was assessed with droplet digital PCR in 159 samples, including primary tumors from 17 tumor classes (reference set) and metastases of known and unknown origin (test set). We combined two different statistical models for class prediction to obtain the most probable TOOs: the nearest shrunken centroids approach of Prediction Analysis of Microarrays (PAMR) and the least absolute shrinkage and selection operator (LASSO) models. The molecular test was successful for all formalin‐fixed paraffin‐embedded samples and provided a TOO identification within 1 week from the biopsy procedure. The most frequently predicted origins were gastrointestinal, pancreas, breast, lung, and bile duct. The assay was applied also to multiple metastases from the same CUP, collected from different metastatic sites: The predictions showed a strong agreement, intrinsically validating our assay. The final CUPs' TOO prediction was compared with the clinicopathological hypothesis of primary site. Moreover, a panel of 13 miRNAs proved to have prognostic value and be associated with overall survival in CUP patients. Our study demonstrated that miRNA expression profiling in CUP samples could be employed as diagnostic and prognostic test. Our molecular analysis can be performed on request, concomitantly with standard diagnostic workup and in association with genetic profiling, to offer valuable indications about the possible primary site, thereby supporting treatment decisions.

Redefining cancer of unknown primary: Is precision medicine really shifting the paradigm?

The concept of Cancer of Unknown Primary (CUP) has evolved with the advent of medical oncology. CUP can be difficult to diagnose and represents 2 to 5% of new cancers, therefore not exceptionally rare. Within CUPs can be identified a subset of favourable prognosis tumours, however the vast majority of CUP patients belongs to a poor prognosis group. CUP features significant oncological challenges, such as unravelling biological and transversal issues, and most importantly, improving patient's outcomes. In that regard, CUP patients' outcomes regrettably showed minimal improvement for decades and CUP remains a cancer group of very poor prognosis. The biology of CUP has two main hypotheses. One is that CUP is a subgroup of a given primary cancer, where the primary is present but cannot be seen due to its small size. The other, the "true" CUP hypothesis, states that CUP share features that make them a specific entity, whatever their tissue of origin. A true biological signature has not yet been described, but chromosomal instability is a hallmark of poor prognosis CUP group. Precision oncology, despite achieving identifying the putative origin of the CUP, so far failed to globally improve outcomes of patients. Targeting molecular pathways based on molecular analysis in CUP management is under investigation. Immunotherapy has not shown ground-breaking results, to date. Accrual is also a crucial issue in CUP trials. Herein we review CUP history, biological features and remaining questions in CUP biology, the two main approaches of molecular oncology in CUP management, in order to draw perspectives in the enormous challenge of improving CUP patient outcomes.

Genomic and epigenomic biomarkers in colorectal cancer: From diagnosis to therapy

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States. Despite ongoing efforts aimed at increasing screening for CRC and early detection, and development of more effective therapeutic regimens, the overall morbidity and mortality from this malignancy remains a clinical challenge. Therefore, identifying and developing genomic and epigenomic biomarkers that can improve CRC diagnosis and help predict response to current therapies are of paramount importance for improving survival outcomes in CRC patients, sparing patients from toxicity associated with current regimens, and reducing the economic burden associated with these treatments. Although efforts to develop biomarkers over the past decades have achieved some success, the recent availability of high-throughput analytical tools, together with the use of machine learning algorithms, will likely hasten the development of more robust diagnostic biomarkers and improved guidance for clinical decision-making in the coming years. In this chapter, we provide a systematic and comprehensive overview on the current status of genomic and epigenomic biomarkers in CRC, and comment on their potential clinical significance in the management of patients with this fatal malignancy, including in the context of precision medicine.

MicroRNA-940 as a Potential Serum Biomarker for Prostate Cancer

Prostate cancer is one of the leading causes of death despite an astoundingly high survival rate for localized tumors. Though prostate specific antigen (PSA) test, performed in conjunction with digital rectal examinations, is reasonably accurate, there are major caveats requiring a thorough assessment of risks and benefits prior to conducting the test. MicroRNAs, a class of small non-coding RNAs, are stable molecules that can be detected in circulation by non-invasive methods and have gained importance in cancer prognosis and diagnosis in the recent years. Here, we investigate circulating miR-940, a miRNA known to play a role in prostate cancer progression, in both cell culture supernatants as well as patient serum and urine samples to determine the utility of miR-940 as a new molecular marker for prostate cancer detection. We found that miR-940 was significantly higher in serum from cancer patients, specifically those with clinically significant tumors (GS ≥ 7). Analysis of receiver operating characteristic curve demonstrated that miR-940 in combination with PSA had a higher area under curve value (AUC: 0.818) than the miR-940 alone (AUC: 0.75) for the diagnosis of prostate cancer. This study provides promising results suggesting the use of miR-940 for prostate cancer diagnosis.

Cell-blocks and other ancillary studies (including molecular genetic tests and proteomics)

Many types of elective ancillary tests may be required to support the cytopathologic interpretations. Most of these tests can be performed on cell-blocks of different cytology specimens. The cell-block sections can be used for almost any special stains including various histochemistry stains and for special stains for different microorganisms including fungi, Pneumocystis jirovecii (carinii), and various organisms including acid-fast organisms similar to the surgical biopsy specimens. Similarly, in addition to immunochemistry, different molecular tests can be performed on cell-blocks. Molecular tests broadly can be divided into two main types Molecular genetic tests and Proteomics.

Cell-blocks and immunohistochemistry

The interpretation of results on immunostained cell-block sections has to be compared with the cumulative published data derived predominantly from formalin-fixed paraffin-embedded (FFPE) tissue sections. Because of this, it is important to recognize that the fixation and processing protocol should not be different from the routinely processed FFPE surgical pathology tissue. Exposure to non-formalin fixatives or reagents may interfere with the diagnostic immunoreactivity pattern. The immunoprofile observed on such cell-blocks, which are not processed in a manner similar to the surgical pathology specimens, may not be representative resulting in aberrant results. The field of immunohistochemistry (IHC) is advancing continuously with the standardization of many immunomarkers. A variety of technical advances such as multiplex IHC with refined methodologies and automation is increasing its role in clinical applications. The recent addition of rabbit monoclonal antibodies has further improved sensitivity. As compared to the mouse monoclonal antibodies, the rabbit monoclonal antibodies have 10 to 100 fold higher antigen affinity. Most of the scenarios involve the evaluation of coordinate immunostaining patterns in cell-blocks with relatively scant diagnostic material without proper orientation which is usually retained in most of the surgical pathology specimens. These challenges are addressed if cell-blocks are prepared with some dedicated methodologies such as NextGen CelBloking™ (NGCB) kits. Cell-blocks prepared by NGCB kits also facilitate the easy application of the SCIP (subtractive coordinate immunoreactivity pattern) approach for proper evaluation of coordinate immunoreactivity. Various cell-block and IHC-related issues are discussed in detail.

Cancer of Unknown Primary in the Molecular Era

Cancer of unknown primary (CUP) is a rare malignancy that presents with metastatic disease and no identifiable site of origin. Most patients have unfavorable features and attempts to treat based on tissue-of-origin identification have not yielded a survival advantage compared with empiric chemotherapy. Next-generation sequencing has revealed genomic alterations that can be targeted in selected cases, suggesting that CUP represents a unique malignancy in which the genomic aberrations may be integral to the diagnosis. Recent trials focusing on tailored combination therapy matched to the genomic alterations in each cancer are providing new avenues of clinical investigation. Here, we discuss recent findings on molecular aberrations in CUP and how the genomic and immune landscape can be leveraged to optimize therapy.

Cancer of Unknown Primary: Challenges and Progress in Clinical Management

Distant metastases are the main cause of cancer-related deaths in patients with advanced tumors. A standard diagnostic workup usually contains the identification of the tissue-of-origin of metastatic tumors, although under certain circumstances, it remains elusive. This disease setting is defined as cancer of unknown primary (CUP). Accounting for approximately 3-5% of all cancer diagnoses, CUPs are characterized by an aggressive clinical behavior and represent a real therapeutic challenge. The lack of determination of a tissue of origin precludes CUP patients from specific evidence-based therapeutic options or access to clinical trial, which significantly impacts their life expectancy. In the era of precision medicine, it is essential to characterize CUP molecular features, including the expression profile of non-coding RNAs, to improve our understanding of CUP biology and identify novel therapeutic strategies. This review article sheds light on this enigmatic disease by summarizing the current knowledge on CUPs focusing on recent discoveries and emerging diagnostic strategies.

miRNA landscape in primary tumors and matched metastases in gastrointestinal stromal tumors

Aim: Gastrointestinal stromal tumor management is extremely challenging, particularly the metastatic disease. The underlying mechanism in metastasis spread remains largely unknown. We aimed to characterize miRNAs involved in the metastatic process in gastrointestinal stromal tumor. Material & methods: Eight primary tumors and 18 synchronous metastases were analyzed through miRNA Taqman arrays or assays. Results: miRNAs profiles revealed similar expression in primary site and metastases. Pair-wise correlation coefficient between primary tumor and metastases was significant for each patient (p < 0.0001 for all profiled patients). Conclusion: Our study, the largest including primary tumors and metastases so far performed, highlighted perpetuation of miRNAs features in metastatic lesions and that the primary origin appears to be the main determinant of the metastases miRNA profile.

Cancer of unknown primary

Cancers of unknown primary (CUPs) are histologically confirmed, metastatic malignancies with a primary tumor site that is unidentifiable on the basis of standard evaluation and imaging studies. CUP comprises 2-5% of all diagnosed cancers worldwide and is characterized by early and aggressive metastasis. Current standard evaluation of CUP requires histopathologic evaluation and identification of favorable risk subtypes that can be more definitively treated or have superior outcomes. Current standard treatment of the unfavorable risk subtype requires assessment of prognosis and consideration of empiric chemotherapy. The use of molecular tissue of origin tests to identify the likely primary tumor site has been extensively studied, and here we review the rationale and the evidence for and against the use of such tests in the assessment of CUPs. The expanding use of next generation sequencing in advanced cancers offers the potential to identify a subgroup of patients who have actionable genomic aberrations and may allow for further personalization of therapy.

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).

Site-Specific and Targeted Therapy Based on Molecular Profiling by Next-Generation Sequencing for Cancer of Unknown Primary Site: A Nonrandomized Phase 2 Clinical Trial

Importance

Although profiling of gene expression and gene alterations by next-generation sequencing (NGS) to predict the primary tumor site and guide molecularly targeted therapy might be expected to improve clinical outcomes for cancer of unknown primary site (CUP), to our knowledge, no clinical trial has previously evaluated this approach.

Objective

To assess the clinical use of site-specific treatment, including molecularly targeted therapy based on NGS results, for patients with CUP.

Design, Setting, and Participants

This phase 2 clinical trial was conducted at 19 institutions in Japan and enrolled 111 previously untreated patients with the unfavorable subset of CUP between March 2015 and January 2018, with 97 patients being included in the efficacy analysis. Eligibility criteria included a diagnosis of unfavorable CUP after mandatory examinations, including pathological evaluation by immunohistochemistry, chest-abdomen-pelvis computed tomography scans, and a positron emission tomography scan.

Interventions

RNA and DNA sequencing for selected genes was performed simultaneously to evaluate gene expression and gene alterations, respectively. A newly established algorithm was applied to predict tumor origin based on these data. Patients received site-specific therapy, including molecularly targeted therapy, according to the predicted site and detected gene alterations.

Main Outcomes And Measures

The primary end point was 1-year survival probability. Secondary end points included progression-free survival (PFS), overall survival (OS), objective response rate, safety, efficacy according to predicted site, and frequency of gene alterations.

Results

Of 97 participants, 49 (50.5%) were women and the median (range) age was 64 (21-81) years. The cancer types most commonly predicted were lung (21 [21%]), liver (15 [15%]), kidney (15 [15%]), and colorectal (12 [12%]) cancer. The most frequent gene alterations were in TP53 (45 [46.4%]), KRAS (19 [19.6%]), and CDKN2A (18 [18.6%]). The 1-year survival probability, median OS, and median PFS were 53.1% (95% CI, 42.6%-62.5%), 13.7 months (95% CI, 9.3-19.7 months), and 5.2 months (95% CI, 3.3-7.1 months), respectively. Targetable EGFR mutations in tumor specimens were detected in 5 patients with predicted non-small-cell lung cancer (5.2%), 4 of whom were treated with afatinib; 2 of these patients achieved a durable PFS of longer than 6 months.

Conclusions and Relevance

This study's findings suggest that site-specific treatment, including molecularly targeted therapy based on profiling gene expression and gene alterations by NGS, can contribute to treating patients with the unfavorable subset of CUP.

Trial Registration

UMIN Identifier: UMIN000016794.

CUP-AI-Dx: A tool for inferring cancer tissue of origin and molecular subtype using RNA gene-expression data and artificial intelligence

BACKGROUND

Cancer of unknown primary (CUP), representing approximately 3-5% of all malignancies, is defined as metastatic cancer where a primary site of origin cannot be found despite a standard diagnostic workup. Because knowledge of a patient's primary cancer remains fundamental to their treatment, CUP patients are significantly disadvantaged and most have a poor survival outcome. Developing robust and accessible diagnostic methods for resolving cancer tissue of origin, therefore, has significant value for CUP patients.

METHODS

We developed an RNA-based classifier called CUP-AI-Dx that utilizes a 1D Inception convolutional neural network (1D-Inception) model to infer a tumor's primary tissue of origin. CUP-AI-Dx was trained using the transcriptional profiles of 18,217 primary tumours representing 32 cancer types from The Cancer Genome Atlas project (TCGA) and International Cancer Genome Consortium (ICGC). Gene expression data was ordered by gene chromosomal coordinates as input to the 1D-CNN model, and the model utilizes multiple convolutional kernels with different configurations simultaneously to improve generality. The model was optimized through extensive hyperparameter tuning, including different max-pooling layers and dropout settings. For 11 tumour types, we also developed a random forest model that can classify the tumour's molecular subtype according to prior TCGA studies. The optimised CUP-AI-Dx tissue of origin classifier was tested on 394 metastatic samples from 11 tumour types from TCGA and 92 formalin-fixed paraffin-embedded (FFPE) samples representing 18 cancer types from two clinical laboratories. The CUP-AI-Dx molecular subtype was also independently tested on independent ovarian and breast cancer microarray datasets FINDINGS: CUP-AI-Dx identifies the primary site with an overall top-1-accuracy of 98.54% in cross-validation and 96.70% on a test dataset. When applied to two independent clinical-grade RNA-seq datasets generated from two different institutes from the US and Australia, our model predicted the primary site with a top-1-accuracy of 86.96% and 72.46% respectively.

INTERPRETATION

The CUP-AI-Dx predicts tumour primary site and molecular subtype with high accuracy and therefore can be used to assist the diagnostic work-up of cancers of unknown primary or uncertain origin using a common and accessible genomics platform.

FUNDING

NIH R35 GM133562, NCI P30 CA034196, Victorian Cancer Agency Australia.

The diagnostic challenges of patients with carcinoma of unknown primary

INTRODUCTION

Cancer of unknown primary (CUP) is a disease entity encompassing heterogeneous malignancies without a clinically-detectable anatomical primary. It is usually a poor prognosis malignancy with dismal prognosis where molecular and genetic testing were expected to be a major breakthrough.

AREAS COVERED

In this review, we provide an overview of the advances in the understanding of the carcinogenesis, biology, diagnosis and treatment of patients with CUP. This review focuses on the advantages and inconveniences of immunohistochemistry and CUP classifiers in assessing the progress in the management of CUP.

EXPERT OPINION

CUP classifiers were expected to gradually replace the classical multistep approach in identifying the culprit tumors to guide site-specific therapy. Immunohistochemistry staining led to the prediction of a single tissue of origin in 10.8-51%. CUP classifiers identified the primary site in 61-89% of these cases and were concordant with immunohistochemistry in 57.1-100%. Immunohistochemistry is cheap, fast and broadly available whereas CUP classifiers are less widely available and have not been validated in randomized control trials. The diagnostic recommendations consist of a standard pathology evaluation based on morphology and algorithmic immunohistochemistry assessment. Physicians should weigh in the input of the CUP classifier to the clinical picture and pathology investigations before performing additional investigations.

Predicting cancer origins with a DNA methylation-based deep neural network model

Cancer origin determination combined with site-specific treatment of metastatic cancer patients is critical to improve patient outcomes. Existing pathology and gene expression-based techniques often have limited performance. In this study, we developed a deep neural network (DNN)-based classifier for cancer origin prediction using DNA methylation data of 7,339 patients of 18 different cancer origins from The Cancer Genome Atlas (TCGA). This DNN model was evaluated using four strategies: (1) when evaluated by 10-fold cross-validation, it achieved an overall specificity of 99.72% (95% CI 99.69%-99.75%) and sensitivity of 92.59% (95% CI 91.87%-93.30%); (2) when tested on hold-out testing data of 1,468 patients, the model had an overall specificity of 99.83% and sensitivity of 95.95%; (3) when tested on 143 metastasized cancer patients (12 cancer origins), the model achieved an overall specificity of 99.47% and sensitivity of 95.95%; and (4) when tested on an independent dataset of 581 samples (10 cancer origins), the model achieved overall specificity of 99.91% and sensitivity of 93.43%. Compared to existing pathology and gene expression-based techniques, the DNA methylation-based DNN classifier showed higher performance and had the unique advantage of easy implementation in clinical settings. In summary, our study shows that DNA methylation-based DNN models has potential in both diagnosis of cancer of unknown primary and identification of cancer cell types of circulating tumor cells.

Progress in refining the clinical management of cancer of unknown primary in the molecular era

Cancer of unknown primary (CUP) is an enigmatic disease entity encompassing heterogeneous malignancies without a detectable primary tumour, despite a thorough diagnostic workup. A minority of patients with CUP (15-20%) can be assigned a putative primary tissue of origin according to clinical and histopathological findings and typically have a more favourable prognosis with the use of corresponding tumour type-specific therapies. Thus, the majority of patients with CUP have disease that cannot be assigned to a culprit primary tumour, are treated with empirical chemotherapy and have a poor prognosis. In the molecular era, the use of (epi)genomic or transcriptomic CUP classifiers and DNA or RNA sequencing offers two, sometimes overlapping, therapeutic strategies: tumour type-specific therapy and biomarker-guided therapy. Published data reveal that the accuracy of site-of-origin predictions made using CUP classifiers ranges between 54% and 98% when compared with the assignment made according to the recommended clinicopathological criteria. These advances have led to promising results in non-randomized prospective studies evaluating the efficacy of tumour type-specific therapy; however, the favourable outcomes were not confirmed in randomized controlled studies comparing this approach with standard empirical chemotherapy. Currently, the evidence supporting the use of biomarker-guided therapies is limited to case reports and small case series. In this Review, we discuss the clinical management of CUP in the era of precision medicine. We focus on the advances in understanding the biology of CUP, the implications for the diagnosis and classification of CUP according to the tissue of origin and the shift away from empirical therapy towards tailored therapy.

Cancer of Unknown Primary Site: Real Entity or Misdiagnosed Disease?

Metastasis is a late event in the progression of any tumour. However, invasive cancers are occasionally detected in the form of metastatic lesions without a clearly detectable primary tumour. Cancer of unknown primary site (CUP) is defined as a confirmed metastatic tumour, with unknown primary tumour site, despite the standardized diagnostic approach that includes clinical history, routine laboratory tests, and complete physical examination. Due to the lack of basic research on its primary causes, CUP is appropriately termed an 'orphan' cancer. Nevertheless, CUP accounts for 2-5% of diagnosed malignancies. To date, it is unclear whether CUP is an entity with primary dormancy as its hallmark or an entity with genetic abnormalities that cause it to manifest as a primary metastatic disease. In this review, we discuss different aspects of CUP, including its current diagnostic methods, angiogenesis effectors, relationship with cancer stem cells and current treatments.

Exploring the biological hallmarks of cancer of unknown primary: where do we stand today?

Cancer of unknown primary (CUP) affects a small percentage of the general population. Nonetheless, a substantial number of these patients have a poor prognosis and consequently succumb to their illness within a year of diagnosis. The natural history of CUP is characterised by early metastasis from the unknown primary site, aggressive course and resistance to conventional chemotherapy. Unfortunately, the processes by which this orphan disease originates and progresses have not been fully elucidated and its biology remain unclear. Despite the conceptual progress in genetic and molecular profiling made over the past decade, recognition of the genetic and molecular abnormalities involved in CUP, as well as the identification of the tissue of origin remain unresolved issues. This review will outline the biology of CUP by exploring the hallmarks of cancer in order to rationalise the complexities of this enigmatic syndrome. This approach will help the reader to understand where research efforts currently stand and the pitfalls of this quest.

Hierarchical Classification of Cancers of Unknown Primary Using Multi-Omics Data

A cancer of unknown primary (CUP) is a metastatic cancer for which standard diagnostic tests fail to locate the primary cancer. As standard treatments are based on the cancer type, such cases are hard to treat and have very poor prognosis. Using molecular data from the metastatic cancer to predict the primary site can make treatment choice easier and enable targeted therapy. In this article, we first examine the ability to predict cancer type using different types of omics data. Methylation data lead to slightly better prediction than gene expression and both these are superior to classification using somatic mutations. After using 3 data types independently, we notice some differences between the classes that tend to be misclassified, suggesting that integrating the data might improve accuracy. In light of the different levels of information provided by different omics types and to be able to handle missing data, we perform multi-omics classification by hierarchically combining the classifiers. The proposed hierarchical method first classifies based on the most informative type of omics data and then uses the other types of omics data to classify samples that did not get a high confidence classification in the first step. The resulting hierarchical classifier has higher accuracy than any of the single omics classifiers and thus proves that the combination of different data types is beneficial. Our results show that using multi-omics data can improve the classification of cancer types. We confirm this by testing our method on metastatic cancers from the MET500 dataset.

Randomized Phase II Trial Comparing Site-Specific Treatment Based on Gene Expression Profiling With Carboplatin and Paclitaxel for Patients With Cancer of Unknown Primary Site

PURPOSE

Although gene expression profiling is a promising diagnostic technique to determine the tissue of origin for patients with cancer of unknown primary site (CUP), no clinical trial has evaluated yet site-specific therapy directed by this approach compared with empirical chemotherapy. We therefore performed a randomized study to assess whether such site-specific therapy improves outcome compared with empirical chemotherapy in previously untreated patients with CUP.

PATIENTS AND METHODS

Comprehensive gene expression profiling was performed by microarray analysis, and an established algorithm was applied to predict tumor origin. Patients with CUP were randomly assigned (1:1) to receive standard site-specific therapy or empirical paclitaxel and carboplatin (PC). The primary end point was 1-year survival rate.

RESULTS

One hundred thirty patients were randomly assigned and had sufficient biopsy tissue for molecular analysis. Efficacy analysis was performed for 50 and 51 patients in the site-specific therapy and empirical PC arms, respectively. Cancer types most commonly predicted were pancreatic (21%), gastric (21%), and lymphoma (20%). The 1-year survival rate was 44.0% and 54.9% for site-specific treatment and empirical PC ( P = .264), respectively. Median overall and progression-free survival were 9.8 and 5.1 months, respectively, for site-specific treatment versus 12.5 and 4.8 months for empirical PC ( P = .896 and .550, respectively). Median overall survival (16.7 v 10.6 months; P = .116) and progression-free survival (5.5 v 3.9 months; P = .018) were better for predicted more-responsive than less-responsive tumor types.

CONCLUSION

Site-specific treatment that was based on microarray profiling did not result in a significant improvement in 1-year survival compared with empirical PC, although prediction of the original site seemed to be of prognostic value.

Molecular characterisation and liquid biomarkers in Carcinoma of Unknown Primary (CUP): taking the 'U' out of 'CUP'

Cancers of Unknown Primary (CUP) comprise a heterogeneous clinical entity of confirmed metastatic cancer where the primary site of origin is undetectable. It has a poor prognosis with limited treatment options. CUP is historically under-researched; however, understanding its biology has the potential to not only improve treatment and survival by implementation of biomarkers for patient management, but also to greatly contribute to our understanding of carcinogenesis and metastasis across all cancer types. Here we review the current advances in CUP research and explore the debated hypotheses underlying its biology. The evolution of molecular profiling and tissue-of-origin classifiers have the potential to transform the diagnosis, classification and therapeutic management of patients with CUP but robust evidence to support widespread use is lacking. Precision medicine has transformed treatment strategy in known tumour types; in CUP, however, there remains a clinical need for a better understanding of molecular characteristics to establish the potential role of novel or existing therapeutics. The emergence of liquid biopsies as a source of predictive and prognostic biomarkers within known tumour types is gaining rapid ground and this review explores the potential utility of liquid biopsies in CUP.

[2018 Consensus statement by the Spanish Society of Pathology and the Spanish Society of Medical Oncology on the diagnosis and treatment of cancer of unknown primary]

Cancer of unknown primary is defined as a heterogeneous group of tumours that present with metastasis, and in which attempts to identify the original site have failed. They differ from other primary tumours in their biological features and how they spread, which means they can be considered a separate entity. There are several hypotheses regarding their origin, but the most plausible explanation for their aggressiveness and chemoresistance seems to involve chromosomal instability. Depending on the type of study done, cancer of unknown primary can account for 2-9% of all cancer patients, mostly 60-75 years old. This article reviews the main clinical, pathological and molecular studies conducted to analyse and determine the origin of cancer of unknown primary. The main strategies for patient management and treatment, by both clinicians and pathologists, are also addressed.

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.

2018 consensus statement by the Spanish Society of Pathology and the Spanish Society of Medical Oncology on the diagnosis and treatment of cancer of unknown primary

Cancer of unknown primary (CUP) is defined as a heterogeneous group of tumours that present with metastasis, and in which attempts to identify the original site have failed. They differ from other primary tumours in their biological features and how they spread, which means that they can be considered a separate entity. There are several hypotheses regarding their origin, but the most plausible explanation for their aggressiveness and chemoresistance seems to involve chromosomal instability. Depending on the type of study done, CUP can account for 2–9% of all cancer patients, mostly 60–75 years old. This article reviews the main clinical, pathological, and molecular studies conducted to analyse and determine the origin of CUP. The main strategies for patient management and treatment, by both clinicians and pathologists, are also addressed.

Prognostic impact of presumed breast or ovarian cancer among patients with unfavorable-subset cancer of unknown primary site

BACKGROUND

The clinical utility and prognostic impact of presumed primary breast or ovarian cancer among patients with an unfavorable subset of cancer of unknown primary site (CUP) remains unclear. We aimed to evaluate the clinical relevance of the presumed primary site of CUP and the clinical outcome of site-specific therapy based on such presumptions.

METHODS

Patients referred to our center who were diagnosed with unfavorable-subset CUP and treated between April 2007 and March 2015 were enrolled in this study. Data were collected retrospectively from the hospital database and electronic medical records. Presumptive primary breast or ovarian cancer was based on histological and immunohistochemical analyses and metastatic patterns. The outcomes of patients with unfavorable-subset CUP with a putative primary site in the breast or ovary (P-CUP) and of patients with unfavorable-subset CUP, but without P-CUP (U-CUP), were assessed.

RESULTS

A total of 780 patients were referred to our hospital with malignancy of unknown origin. Of these, 409 patients were diagnosed with CUP and 344 patients with unfavorable-subset CUP. Following clinicopathological examination, 40 (11.6%) of the 344 patients had P-CUP and the remaining 303 (88.3%) patients had U-CUP. In total, 136 patients received chemotherapy (22 with P-CUP and 114 with U-CUP). Among the 22 patients with P-CUP, three received hormonal therapy for breast cancer, and 19 received chemotherapy based on the presumed primary organ (breast, 4; ovaries, 15). Conventional platinum-based chemotherapy was administered to 105 patients with U-CUP and non-platinum drug treatment to nine patients. The objective response rates were 61.1% (95% confidence interval [CI]: 38.6-83.6) and 41.1% (95% CI: 31.8-50.4) for patients with P-CUP and U-CUP, respectively. The median overall survival durations were 50.0 months and 16.9 months (log-rank: P = 0.002) for patients with P-CUP and U-CUP, respectively. P-CUP was identified as an independent predictor of good prognosis according to multivariate analysis.

CONCLUSIONS

Patients with P-CUP had higher response rates and a better prognosis compared with patients with U-CUP. It might thus be reasonable to classify this subset as a new category of CUP with a favorable prognosis.

Precision medicine based on epigenomics: the paradigm of carcinoma of unknown primary

Epigenetic alterations are a common hallmark of human cancer. Single epigenetic markers are starting to be incorporated into clinical practice; however, the translational use of these biomarkers has not been validated at the 'omics' level. The identification of the tissue of origin in patients with cancer of unknown primary (CUP) is an example of how epigenomics can be incorporated in clinical settings, addressing an unmet need in the diagnostic and clinical management of these patients. Despite the great diagnostic advances made in the past decade, the use of traditional diagnostic procedures only enables the tissue of origin to be determined in ∼30% of patients with CUP. Thus, development of molecularly guided diagnostic strategies has emerged to complement traditional procedures, thereby improving the clinical management of patients with CUP. In this Review, we present the latest data on strategies using epigenetics and other molecular biomarkers to guide therapeutic decisions involving patients with CUP, and we highlight areas warranting further research to engage the medical community in this unmet need.

Next generation sequencing of carcinoma of unknown primary reveals novel combinatorial strategies in a heterogeneous mutational landscape

BACKGROUND

Advanced carcinoma of unknown primary (CUP) has limited effective therapeutic options given the phenotypic and genotypic diversity. To identify future novel therapeutic strategies we conducted an exploratory analysis of next-generation sequencing (NGS) of relapsed, refractory CUP.

METHODS

We identified patients in our phase I clinic where archival tissue was available for a targeted NGS CLIA-certified assay.

RESULTS

Of 17 patients tested, 15 (88%) demonstrated genomic alterations (median 2 aberrations; range 0-8, total 59 alterations). Nine (53%) patients had altered cell signaling including the PI3K/AKT/MTOR (n=5, 29%) and MAPK pathways (n=3,18%); 7 (41%) patients demonstrated ≥1 alterations in tumor suppressor genes (TP53 in 5 patients), 8 (47%) had impaired epigenetic regulation and DNA methylation, 8 (47%) had aberrant cell cycle regulation, commonly in the cyclin dependent kinases. Ten (59%) patients had alterations in transcriptional regulators. Concurrent mutations affecting cell cycle regulation were noted to occur with aberrant epigenetic regulation (n=6, 35%) and MAPK/PI3K pathway (n=5, 29%).

CONCLUSION

Every patient had a unique molecular profile with no two patients demonstrating an identical panel of mutations. We identify two emerging novel combinatorial strategies targeting impaired cell cycle arrest, first with epigenetic modifiers and, second, with MAPK/PI3K pathway inhibition.

Prognostic clinicopathologic factors in carcinoma of unknown primary origin: a study of 106 consecutive cases

A heterogeneous group of cancers for which the site of origin remains occult after detailed investigations is defined as carcinomas of unknown primary origin (CUPs). Because patients with CUP have a dismal prognosis, we have analyzed CUPs to highlight the implication of clinicopathologic factors related with patient survival. A total of 106 consecutive cases of CUP were collected. A two-step strategy of immunohistochemistry to assess CUPs according NCCN Guidelines is used to separate carcinomatous tumors and subtype carcinomas. Median follow up of censored patients was 26 months. Median survival time of whole patients was 13 months (95% confidence interval [CI], 8.43 - 19.1 months), with one, two and five-year survival rate of 53.7%, 35.1%, and 30.5%, respectively. Factors related with shorter overall survival was adenocarcinoma histology (P=0.001), increased CA19-9 (P=0.003), increased CEA (P=0.047), increased LDH (P<0.001), CK20 positivity (P=0.002), presence of bone metastasis (P=0.017), metastasis not confined to the lymph nodes (P=0.015), unfavorable clinical group based predefined category (P=0.017), and patients with no treatment (P<0.001). Multivariable analysis with cox regression model revealed factors related with overall survival; cases belonged to Culine’s poor risk group (HR, 3.88; 95% CI, 1.75-8.64; P=0.001) and CK20 positivity (HR, 3.31; 95% CI, 1.42-7.70; P=0.005). In conclusion, the CK20 expression profile is a prognostic factor in patients with CUP and initial stratification of patient with Culine’s model may provide a prognostic information in these patients. Assessment of clinical implication of these factors in the context of site specific therapy needs to be evaluated.

Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis

BACKGROUND

Cancer of unknown primary ranks in the top ten cancer presentations and has an extremely poor prognosis. Identification of the primary tumour and development of a tailored site-specific therapy could improve the survival of these patients. We examined the feasability of using DNA methylation profiles to determine the occult original cancer in cases of cancer of unknown primary.

METHODS

We established a classifier of cancer type based on the microarray DNA methylation signatures (EPICUP) in a training set of 2790 tumour samples of known origin representing 38 tumour types and including 85 metastases. To validate the classifier, we used an independent set of 7691 known tumour samples from the same tumour types that included 534 metastases. We applied the developed diagnostic test to predict the tumour type of 216 well-characterised cases of cancer of unknown primary. We validated the accuracy of the predictions from the EPICUP assay using autopsy examination, follow-up for subsequent clinical detection of the primary sites months after the initial presentation, light microscopy, and comprehensive immunohistochemistry profiling.

FINDINGS

The tumour type classifier based on the DNA methylation profiles showed a 99·6% specificity (95% CI 99·5-99·7), 97·7% sensitivity (96·1-99·2), 88·6% positive predictive value (85·8-91·3), and 99·9% negative predictive value (99·9-100·0) in the validation set of 7691 tumours. DNA methylation profiling predicted a primary cancer of origin in 188 (87%) of 216 patients with cancer with unknown primary. Patients with EPICUP diagnoses who received a tumour type-specific therapy showed improved overall survival compared with that in patients who received empiric therapy (hazard ratio [HR] 3·24, p=0·0051 [95% CI 1·42-7·38]; log-rank p=0·0029).

INTERPRETATION

We show that the development of a DNA methylation based assay can significantly improve diagnoses of cancer of unknown primary and guide more precise therapies associated with better outcomes. Epigenetic profiling could be a useful approach to unmask the original primary tumour site of cancer of unknown primary cases and a step towards the improvement of the clinical management of these patients.

FUNDING

European Research Council (ERC), Cellex Foundation, the Institute of Health Carlos III (ISCIII), Cancer Australia, Victorian Cancer Agency, Samuel Waxman Cancer Research Foundation, the Health and Science Departments of the Generalitat de Catalunya, and Ferrer.

Performance and prognostic utility of the 92-gene assay in the molecular subclassification of ampullary adenocarcinoma

Background

Ampullary adenocarcinoma is a rare gastrointestinal cancer associated with diverse outcomes due to clinical and pathological heterogeneity. Standardized methods to better prognosticate and inform therapeutic selection for ampullary adenocarcinoma are needed. This study explored the novel use and potential prognostic utility of a 92-gene cancer classifier in ampullary adenocarcinomas.

Methods

In this prospectively-defined, blinded study of ampullary adenocarcinoma [N =54; stage T3 or higher (57 %); Grade III (44 %); Node positive (55 %)], the performance of a 92-gene classifier was examined to predict the ampullary subtype that was derived from histomorphological examination of resected ampullary samples. Outcome data for relapse-free survival (RFS) and overall survival (OS) were plotted to compare the prognostic utility of histological subtyping, histomolecular phenotyping, and the 92-gene classifier. Multivariate analysis was used to determine clinicopathological variables that were independently associated with overall survival.

Results

The 92-gene classifier demonstrated sensitivities and specificities of 85 % [95 % CI, 66–94] and 68 % [95 % CI, 48–84] and 64 % [95 % CI, 46–79] and 88 % [95 % CI, 70–98] for the pancreaticobiliary and intestinal histological subtypes, respectively. For the 92-gene classifier, improved outcomes were observed for the intestine versus the pancreaticobiliary prediction (median OS 108.1 v 36.4 months; HR, 2.17; 95 % CI, 0.98 to 4.79; P = 0.05). Similar results were seen for ampullary adenocarcinoma stratification by histological subtype (P = 0.04) and histomolecular phenotype (P = 0.02). Within poorly differentiated ampullary adenocarcinomas only the 92-gene classifier demonstrated statistically significant differences in RFS and OS (P < 0.05).

Conclusions

Prognostic stratification of ampullary adenocarcinoma was similar for the 92-gene classifier, histological subtype, and histomolecular phenotype. The 92-gene classifier provides an unbiased standardized molecular-based approach to stratify ampullary tumors.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2677-3) contains supplementary material, which is available to authorized users.

Precision oncology: origins, optimism, and potential

Imatinib, the first and arguably the best targeted therapy, became the springboard for developing drugs aimed at molecular targets deemed crucial to tumours. As this development unfolded, a revolution in the speed and cost of genetic sequencing occurred. The result--an armamentarium of drugs and an array of molecular targets--set the stage for precision oncology, a hypothesis that cancer treatment could be markedly improved if therapies were guided by a tumour's genomic alterations. Drawing lessons from the biological basis of cancer and recent empirical investigations, we take a more measured view of precision oncology's promise. Ultimately, the promise is not our concern, but the threshold at which we declare success. We review reports of precision oncology alongside those of precision diagnostics and novel radiotherapy approaches. Although confirmatory evidence is scarce, these interventions have been widely endorsed. We conclude that the current path will probably not be successful or, at a minimum, will have to undergo substantive adjustments before it can be successful. For the sake of patients with cancer, we hope one form of precision oncology will deliver on its promise. However, until confirmatory studies are completed, precision oncology remains unproven, and as such, a hypothesis in need of rigorous testing.

Cancer of unknown primary ultimately diagnosed as male breast cancer: A rare case report

Cancers of unknown primary (CUP) constitute a significant diagnostic and therapeutic challenge for clinicians and a frequent cause of cancer-related mortality in Western countries. Immunohistochemistry assays are commonly used to identify the primary cancer, but fail in approximately one-third of cases. The identification of the possible origin of CUP is crucial, as it may help select the appropriate treatment options. We herein present the case of a 54-year-old male patient, who presented with lower back pain in June, 2013. Following a thorough investigation, the clinical and pathological findings could not identify the primary cancer, leading towards a misdiagnosis. Ultimately, microRNA testing of the resected spine lesion was able to identify the primary tumor as male breast cancer and allow for optimal treatment of the patient.

Cancer of Unknown Primary in Adolescents and Young Adults: Clinicopathological Features, Prognostic Factors and Survival Outcomes

Background

Cancer in adolescents and young adults (AYAs) (15–39 years) is increasingly recognized as a distinct clinical and biological entity. Cancer of unknown primary (CUP), a disease traditionally presenting in older adults with a median age of 65 years, poses several challenges when diagnosed in AYA patients. This study describes clinicopathological features, outcomes and challenges in caring for AYA-CUP patients.

Methods

A retrospective review of 47 AYAs diagnosed with CUP at MD Anderson Cancer Center (6/2006–6/2013) was performed. Patients with favorable CUP subsets treated as per site-specific recommendations were excluded. Demographics, imaging, pathology and treatment data was collected using a prospectively maintained CUP database. Kaplan-Meier product limit method and log-rank test were used to estimate and compare overall survival. The cox-proportional model was used for multivariate analyses.

Results

Median age was 35 years (range 19–39). All patients underwent comprehensive workup. Adenocarcinoma was the predominant histology (70%). A median of 9 immunostains (range 2–29) were performed. The most common putative primary was biliary tract based on clinicopathological parameters as well as gene profiling. Patients presented with a median of 2 metastatic sites [lymph node (60%), lung (47%), liver (38%) and bone (34%)]. Most commonly used systemic chemotherapies included gemcitabine, fluorouracil, taxanes and platinum agents. Median overall survival for the entire cohort was 10.0 (95% confidence interval (CI): 6.7–15.4) months. On multivariate analyses, elevated lactate dehydrogenase (Hazard ratio (HR) 3.66; 95%CI 1.52–8.82; P = 0.004), ≥3 metastatic sites (HR 5.34; 95%CI 1.19–23.9; P = 0.029), and tissue of origin not tested (HR 3.4; 95%CI 1.44–8.06; P = 0.005) were associated with poor overall survival. Culine’s CUP prognostic model (lactate dehydrogenase, performance status, liver metastases) was validated in this cohort (median overall survival: good-risk 25.2 months vs. poor-risk 6.1 months).

Conclusions

AYA-CUP is associated with a poor prognosis. In the current “-omics” era collaborative research efforts towards understanding tumor biology and therapeutic targets in AYA-CUP is an unmet need, necessary for improving outcomes in young CUP patients.

Translating cancer genomes and transcriptomes for precision oncology

Understanding the molecular landscape of cancer has facilitated the development of diagnostic, prognostic, and predictive biomarkers for clinical oncology. Developments in next-generation DNA sequencing technologies have increased the speed and reduced the cost of sequencing the nucleic acids of cancer cells. This has unlocked opportunities to characterize the genomic and transcriptomic landscapes of cancer for basic science research through projects like The Cancer Genome Atlas. The cancer genome includes DNA-based alterations, such as point mutations or gene duplications. The cancer transcriptome involves RNA-based alterations, including changes in messenger RNAs. Together, the genome and transcriptome can provide a comprehensive view of an individual patient's cancer that is beginning to impact real-time clinical decision-making. The authors discuss several opportunities for translating this basic science knowledge into clinical practice, including a molecular classification of cancer, heritable risk of cancer, eligibility for targeted therapies, and the development of innovative, genomic-based clinical trials. In this review, key applications and new directions are outlined for translating the cancer genome and transcriptome into patient care in the clinic.

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.

Cancers of unknown primary origin (CUP) are characterized by chromosomal instability (CIN) compared to metastasis of know origin

Background

Cancers of unknown primary (CUPs) constitute ~5% of all cancers. The tumors have an aggressive biological and clinical behavior. The aim of the present study has been to uncover whether CUPs exhibit distinct molecular features compared to metastases of known origin.

Methods

Employing genome wide transcriptome analysis, Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA), we defined the putative origins of a large series of CUP and how closely related a particular CUP was to corresponding metastases of known origin. LDA predictions were subsequently used to define a universal CUP core set of differentially expressed genes, that by means of gene set enrichment analysis was exploited to depict molecular pathways characterizing CUP.

Results

The analyses show that CUPs are distinct from metastases of known origin. CUPs exhibit inconsistent expression of conventional cancer biomarkers and QDA derived outlier scores show that CUPs are more distantly related to their primary tumor class than corresponding metastases of known origin. Gene set enrichment analysis showed that CUPs display increased expression of genes involved in DNA damage repair and mRNA signatures of chromosome instability (CIN), indicating that CUPs are chromosome unstable compared to metastases of known origin.

Conclusions

CIN may account for the uncommon clinical presentation, chemoresistance and poor outcome in patients with CUP and warrant selective diagnostic strategies and treatment.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1128-x) contains supplementary material, which is available to authorized users.

Clinicians' expectations for gene-driven cancer therapy

A new era of medicine is rapidly approaching, which will change not only pathological diagnosis but also medical decision-making. This paper raises the question of how well prepared doctors are to address the new issues that will soon confront them. The human genome has been completely sequenced and general understanding about cancer biology has increased enormously with understanding that unregulated gene function and complicated changes in signal pathways are related to uncontrolled cell growth. Thus, gene-driven therapy involving alterations to genes are recognized to present new therapy options. This advance will necessitate major changes to the decision-making aspect of physicians. This article focuses on defining the pertinent changes and addressing what they mean for practicing physicians.

microRNA levels in paraffin-embedded indolent B-cell non-Hodgkin lymphoma tissues from patients chronically infected with hepatitis B or C virus

Background

Epidemiological evidence links Hepatitis B Virus (HBV) and Hepatitis C Virus (HCV) to B-cell non-Hodgkin lymphoma (B-NHL). These B-NHLs, particularly those associated with HCV, may represent a distinct sub-group with peculiar molecular features, including peculiar expression of microRNAs (miRs).

The aim of the present study was to search for miRs whose level in indolent B-NHL tissues could be associated with HBV or HCV infection.

Methods

Fourteen formalin fixed paraffin embedded (FFPE) tissues from HBV+, HCV+ and HBV-/HCV- indolent B-NHL patients were analyzed for levels of 34 selected miRs by quantitative Real-Time PCR. Reactive lymph nodes (RLNs) from HBV-/HCV- patients were included as non-tumor control. Statistical analysis of output data included Pearson and Spearman correlation and Mann-Whitney test and were carried out by the STATA software.

Results

MiR-92a was decreased exclusively in HBV-/HCV- B-NHLs, while miR-30b was increased in HBV+ and HCV+ samples, though only the HCV+ achieved full statistical significance. Analysis of a small subset of B-NHLs belonging to the same histological subtype (Nodal Marginal Zone Lymphoma) highlighted three miRs associated with HCV infection (miR-223, miR-29a and miR-29b) and confirmed decreased level of miR-92a in HBV-/HCV- samples also when considering this restricted B-NHL group.

Conclusions

Although caution is needed due to the limited number of analyzed samples, overall the results suggest that differences at the miR expression level exist between indolent B-NHLs developed in patients with or without HBV or HCV infection. The identification of three further miRs associated with HCV by analyzing histologically homogeneous samples suggests that variations of miR levels possibly associated with HBV or HCV may be obscured by the tissue-specific variability of miR level associated with the different histological subtypes of B-NHL. Thus, the identification of further miRs will require, in addition to an increased sample size, the comparison of B-NHL tissues with the same histological classification.