| Literature DB >> 30580378 |
Alicia-Marie Conway1,2,3, Claire Mitchell1,2, Elaine Kilgour2,3, Gerard Brady2,3, Caroline Dive2,3, Natalie Cook4,5.
Abstract
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.Entities:
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Year: 2018 PMID: 30580378 PMCID: PMC6342985 DOI: 10.1038/s41416-018-0332-2
Source DB: PubMed Journal: Br J Cancer ISSN: 0007-0920 Impact factor: 7.640
Fig. 1Current management and treatment options for favourable and unfavourable subtypes of CUP. Following tissue biopsy diagnosis of confirmed CUP, patients with favourable clinical features are treated as the analogous tumour type. Those patients within the unfavourable clinical subtype can be offered palliative chemotherapy if they have good performance status. There is no standard second line therapy. IHC immunohistochemistry, PS performance status, CK cytokeratin, LDH lactate dehydrogenase, SCC squamous cell carcinoma
Selected tissue-of-origin studies applied to CUP using molecular profiling of tumour tissue DNA (adapted from 1)
| Study type; Lead author, year; Ref. | No. of patients profiled/ enrolled | Method analysis | No of tumour types | Prediction accuracy | Commonest predicted tumour types | Validation / Impact on clinical outcomes with prediction-based treatment |
|---|---|---|---|---|---|---|
| Retrospective; Horlings, 2008[ | 38 | GEM; RNA | 10 | 61%-93% | Lung (24%); CRC (18%); Pancreas (16%); Ovarian (11%) | Clinicopathological features and IHC / ND |
| Retrospective /prospective; Varadhachary, 2008[ | 104/120 | 10-gene qRT-PCR; RNA | 6 | 61% | CRC (49%); NSCLC (33%); Pancreas (21%); Ovarian (14%) | Clinicopathological features / Improved OS of prospective vs retrospective cohort |
| Prospective; Varadhachary, 2011[ | 74/104 | 48-microRNA qRT-PCR | 17 | 84% | CRC ( | Clinicopathological features and IHC / ND |
| Retrospective; Fernandez, 2012[ | 42 | DNA methylation array | 19 | 78% (7/9 tumours) | CRC (34%); NSCLC (17%); Breast (17%) | Clinicopathological features / ND |
| Retrospective, Hainsworth, 2012[ | 42 predicted to be CRC | 92-gene qRT-PCR, RNA | 30 | 54-86% | Only studied CRC | Clinicopathological features / ND |
| Retrospective; Pentheroudakis 2013[ | 85/93 | 64 microRNA | 42 | 92% | ND | Clinicopathological features and IHC / ND |
| Prospective; Hainsworth, 2013[ | 252/289 | 92-gene qRT-PCR; RNA | 30 | ND | Biliary tract (18%); CRC (10%); NSCLC (7%); Breast (5%); Urothelial (11%); Pancreatic (5%) | ND / Improved OS compared to historical controls |
| Retrospective; Tothill, 2015[ | 49 | GEM; RNA | 18 | 78% | SCC ( | Clinicopathological features / ND |
| Prospective phase II; Yoon, 2016[ | 38/46 | 2000-gene GEM; RNA | 15 | ND | NSCLC (21%); CRC (18%); Ovarian (18%); Pancreas (16%) | ND / Improved OS in platinum-responsive tumour types |
| Retrospective; Moran, 2016[ | 216 | EPICUP DNA methylation array | 38 | 87-100% | NSCLC (20%); Head and neck SCC. (10%); Breast (9%); CRC (9%); HCC (7%); Pancreatic (7%) | Latent primary, clinicopathological features, autopsy / Improved OS some patients ( |
CRC colorectal cancer, GEM gene expression microarray, HCC hepatocellular carcinoma, IHC immunohistochemistry, NSCLC non-small cell lung cancer, ND not done, OS overall survival, qRT-PCR quantitative reverse transcription polymerase chain reaction
Summary of genetic aberrations found within CUP tumours from tissue biopsy
| Year; Ref. | Technique | No. of patients | % of samples with at least one genomic aberration | % potentially therapeutically targetable mutation | Most common genetic aberrations |
|---|---|---|---|---|---|
| 2015;[ | Retrospective DNA sequencing 236 genes and 47 introns from FFPE (based on FoundationOne assay) | 200 | 96% | 20% | |
| 2014;[ | Retrospective gene mutation analysis (47 genes) and protein expression from tumour tissue | 1806 | ND | 96%a | |
| 2013;[ | Retrospective DNA sequencing (701 genes) and CNA of tumour tissue | 16 | 100% | 81% | |
| 2014;[ | CTNNB1, MET, PIK3CA, KRAS, BRAF mutation targeted sequencing from FFPE | 87 | 66% | 36.9%b | |
| 2016;[ | Retrospective 50 targeted genes and copy number analysis | 55 | 84% | 15% | |
| 2017;[ | Next generation sequencing of tumour tissue | 17 | 88% | 41% | Impaired |
| Epigenetic deregulation (47%) | |||||
| Impaired cell cycle control (47%) | |||||
| 2018;[ | Retrospective 592-gene NextSeq platform panel | 389 | ND | 22% | |
ARID1A AT-Rich interaction domain 1 A, BRCA2 breast cancer 2 gene, CDKN2A cyclin-dependent kinase Inhibitor 2A, CAN copy number analysis, CTNNB1 catenin beta-1, EGFR epidermal growth factor receptor, FFPE fresh frozen paraffin embedded, KRAS Kirsten rat sarcoma Viral Oncogene Homolog, ND not documented, PIK3CA p100α catalytic subunit 1A phosphatidylinositol 3-kinase, pts patients; ref. reference, STK11 serine/threonine Kinase 11, TP53 tumour protein 53
aBased on mutations and protein expression profiles indicated therapeutic benefit of targeted agents, cytotoxics and immunotherapy
bProportion of patients with activating mutations
Fig. 2Potential clinical and research applications of liquid biopsies for the management of CUP. Clinical and research applications of liquid biopsies are wide-reaching, from early detection and diagnosis to monitoring response to therapy and earlier detection of disease relapse. Liquid biopsies contain genetic information from the tumour in the form of circulating tumour cells (CTCs), tumour-educated platelets (TEPs), mircoRNAs contained within exomes and circulating free tumour DNA (ctDNA). ctDNA is a component of circulating free DNA (cfDNA); fragments of DNA either passively released by cells as a consequence of apoptosis and cell death, or actively released by cells as a potential messaging signal.[111] Patients with cancer have a much higher proportion of cfDNA in the blood compared with healthy normal volunteers (HNV); a greater proportion is tumour-derived ctDNA that is shed from the highly proliferating tumour cells and/or tumour cell death.[112,113] CTCs are released into the bloodstream by a passive process of tumour shedding or through active intravasation, including processes such as epithelial-to-mesenchymal transition (EMT), cell-to-cell cooperation and vasculogenic mimicry.[91,92] Epithelial cells undergoing EMT lose their characteristic cell-to-cell interactions, become mobile and gain invasive properties. CTCs that underwent EMT may reverse this process during the process of metastasis formation; however, only a very small proportion of CTCs subsequently propagate a distant metastasis.[74] Molecular analyses that can be performed on genetic material include copy number alterations, actionable mutation detection, amplifications, and deletions, as well as epigenetic and transcriptome analysis. CTCs can be implanted into immune-compromised mice as CTC explants (CDX) or cultured directly as CTC organoids for drug testing
Summary of liquid biopsy research in CUP and blood-based Tissue-of-Origin studies
| Lead Author; Year; ref. | Liquid biopsy approach | Patients included | Study results |
|---|---|---|---|
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| Allard; 2004[ | CTC enumeration (CellSearch®) | 964 cancer patients (11 CUP); 244 non-malignant/healthy individuals | CTCs detected in 52% of CUP samples (n = 27); mean CTC count 16 ( + /-35). The second highest proportion of positive samples amongst tumour types. |
| Komine; 2014[ | CTC enumeration (CellSearch®) | 10 patients with CUP (5 treatment naive) | CTCs detected in 50% of samples. CTC counts 3-207 (median = 31). CTC count declined with treatment in one patient |
| Pentheroudakis; 2012[ | CTC (IF detection) | 24 patients with CUP | CTCs detected in 15/24 (62.5%) patients but of no prognostic value |
| Kato; 2017[ | cfDNA mutational profile | 442 patients with CUP | Targeted NGS (up to 70 genes) detected mutations in 66% of patients. The most common alterations were: |
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| Best; 2015[ | TEPs | 55 healthy donors; Tumour types: 60 NSCLC; 41 CRC; 39 glioblastoma; 35 pancreatic cancer; 39 breast cancer; 14 HPB cancer | mRNA profiles of TEPs able to predict tissue of origin from 6 primary tumour types by support vector machine classifier with median accuracy of 73% |
| Klein; 2018[ | cfDNA | 749 controls; 878 cancer cases:28 CRC; 19 oesophageal; 5 Head and neck; 5 HPB; 73 lung; 17 lymphoma; 11 MM; 10 ovarian; 10 pancreatic | Targeted NGS (507 genes), copy number variation, whole genome bisulfite sequencing. Sensitivity 60-90% in detecting cancer in those tumour types (stages I-III) |
| Cohen; 2018[ | cfDNA | 626 cancer cases (ovarian, lung, liver, stomach, pancreatic, breast, CRC, oesophageal); 812 healthy donors | 16 gene and 8 tumour protein panel (CancerSEEK) identified the cancer type by supervised machine learning in a median of 69-98% of patients |
| Sun; 2015[ | cfDNA | 29 HCC patients; 32 control subjects | Plasma DNA tissue mapping from cfDNA methylation patterns determined liver tissue contribution was higher in HCC patients compared to controls. |
| Lehmann-Werman; 2016[ | cfDNA | 42 patients with pancreatic cancer; 47 healthy subjects | cfDNA methylation patterns of pancreatic cell death identified in 20/42 patients with pancreatic cancer. Performed better than cfDNA |
| Guo; 2017[ | cfDNA | 75 normal individuals; 29 lung cancer; 30 CRC | cfDNA methylation patterns predicted tissue of origin in 82.8% of CRC samples and 88.5% of lung cancer patients |
| Matthew; 2016[ | CTCs enrichment (CellSearch®) | 2 patients with breast cancer; 1 patient with prostate cancer | IHC staining of isolated CTCs able to determine tissue of origin in breast and prostate cancer using CK7, CK20, TTf-1, ER, PSA stains. |
| Lu; 2016[ | CTC enrichment (CMx chip) | 12 healthy individuals; 13 patients with cancer (lung, CRC and prostate) | Distiguished cancer from healthy individuals and determined tissue of origin by IHC staining of CK7, CK20, TF-1, CDX2 and PSA. |
cfDNA circulating-free DNA, CDX2 caudal Type Homeobox 2, CK cytokeratin, CRC colorectal carcinoma, CTC circulating tumour cells, CUP cancer of unknown primary, HCC hepatocellular carcinoma, HPB hepatobiliary, IF immunofluorescence, KRAS Kirsten rat sarcoma viral oncogene homolog, MM multiple myeloma, NGS next-generation sequencing, NSCLC non-small cell lung cancer, PIK3C p100α catalytic subunit 1 A phosphatidylinositol 3-kinase, PSA prostate specific antigen, ref. reference, TEP tumour-educated platelet, TP53 tumour protein 53, TTF1 thyroid transcription factor 1
Fig. 3Proposed role of liquid biopsies in CUP research and future diagnosis, management stratification and monitoring of CUP patients. A single blood test at presentation of CUP could determine tissue of origin, evaluate prognostic and predictive biomarkers and stratify patients to appropriate treatment. Serial blood samples could monitor early response to therapy or resistance, enabling timely switch or halting of futile treatments. EGFR epidermal growth factor receptor, IHC immunohistochemistry, MSI microsatellite instability, PS performance status.