Extracellular Vesicle and Particle Biomarkers Define Multiple Human Cancers.

There is an unmet clinical need for improved tissue and liquid biopsy tools for cancer detection. We investigated the proteomic profile of extracellular vesicles and particles (EVPs) in 426 human samples from tissue explants (TEs), plasma, and other bodily fluids. Among traditional exosome markers, CD9, HSPA8, ALIX, and HSP90AB1 represent pan-EVP markers, while ACTB, MSN, and RAP1B are novel pan-EVP markers. To confirm that EVPs are ideal diagnostic tools, we analyzed proteomes of TE- (n = 151) and plasma-derived (n = 120) EVPs. Comparison of TE EVPs identified proteins (e.g., VCAN, TNC, and THBS2) that distinguish tumors from normal tissues with 90% sensitivity/94% specificity. Machine-learning classification of plasma-derived EVP cargo, including immunoglobulins, revealed 95% sensitivity/90% specificity in detecting cancer. Finally, we defined a panel of tumor-type-specific EVP proteins in TEs and plasma, which can classify tumors of unknown primary origin. Thus, EVP proteins can serve as reliable biomarkers for cancer detection and determining cancer type.

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.

PathMethy: an interpretable AI framework for cancer origin tracing based on DNA methylation.

Despite advanced diagnostics, 3%-5% of cases remain classified as cancer of unknown primary (CUP). DNA methylation, an important epigenetic feature, is essential for determining the origin of metastatic tumors. We presented PathMethy, a novel Transformer model integrated with functional categories and crosstalk of pathways, to accurately trace the origin of tumors in CUP samples based on DNA methylation. PathMethy outperformed seven competing methods in F1-score across nine cancer datasets and predicted accurately the molecular subtypes within nine primary tumor types. It not only excelled at tracing the origins of both primary and metastatic tumors but also demonstrated a high degree of agreement with previously diagnosed sites in cases of CUP. PathMethy provided biological insights by highlighting key pathways, functional categories, and their interactions. Using functional categories of pathways, we gained a global understanding of biological processes. For broader access, a user-friendly web server for researchers and clinicians is available at https://cup.pathmethy.com.

Synergic activity of FGFR2 and MEK inhibitors in the treatment of FGFR2-amplified cancers of unknown primary.

Patients with cancer of unknown primary (CUP) carry the double burden of an aggressive disease and reduced access to therapies. Experimental models are pivotal for CUP biology investigation and drug testing. We derived two CUP cell lines (CUP#55 and #96) and corresponding patient-derived xenografts (PDXs), from ascites tumor cells. CUP cell lines and PDXs underwent histological, immune-phenotypical, molecular, and genomic characterization confirming the features of the original tumor. The tissue-of-origin prediction was obtained from the tumor microRNA expression profile and confirmed by single-cell transcriptomics. Genomic testing and fluorescence in situ hybridization analysis identified FGFR2 gene amplification in both models, in the form of homogeneously staining region (HSR) in CUP#55 and double minutes in CUP#96. FGFR2 was recognized as the main oncogenic driver and therapeutic target. FGFR2-targeting drug BGJ398 (infigratinib) in combination with the MEK inhibitor trametinib proved to be synergic and exceptionally active, both in vitro and in vivo. The effects of the combined treatment by single-cell gene expression analysis revealed a remarkable plasticity of tumor cells and the greater sensitivity of cells with epithelial phenotype. This study brings personalized therapy closer to CUP patients and provides the rationale for FGFR2 and MEK targeting in metastatic tumors with FGFR2 pathway activation.

A Fast, Affordable, and Minimally Invasive Diagnostic Test for Cancer of Unknown Primary Using DNA Methylation Profiling.

Currently, we cannot provide a conclusive diagnosis for 3% to 5% of people who are confronted with cancer. These patients have cancer of unknown primary (CUP), ie, a metastasized cancer for which the tissue of origin cannot be determined. Studies have shown that the DNA methylation profile is a unique "fingerprint" that can be used to classify tumors. Here we used cell-free reduced representation bisulfite sequencing (cfRRBS), a technique that allows us to identify the methylation profile starting from minimal amounts of highly fragmented DNA, for CUP diagnosis on formalin-fixed paraffin-embedded (FFPE) tissue and liquid biopsies. We collected 80 primary tumor FFPE samples covering 16 tumor entities together with 15 healthy plasma samples to use as a custom cfRRBS reference data set. Entity-specific methylation regions are defined for each entity to build a classifier based on nonnegative least squares deconvolution. This classification framework was tested on 30 FFPE, 19 plasma, and 40 pleural and peritoneal effusion samples of both known metastatic tumors and clinical CUPs for which pathological investigation finally resulted in a cancer diagnosis. Using this framework, 27 of 30 FFPE (all CUPs) and 16 of 19 plasma samples (10/13 CUPs) obtained an accurate diagnosis, with a minimal DNA input of 400 pg. Diagnosis of the 40 pleural and peritoneal effusion samples is possible in 9 of 27 samples with negative/inconclusive cytology (6/13 CUPs), showing that cell-free DNA (cfDNA) methylation profiling could complement routine cytologic analysis. However, a low "cfDNA - high-molecular weight DNA ratio" has a considerable impact on the prediction accuracy. Moreover, the accuracy improves significantly if the predicted tumor percentage is >7%. This proof-of-concept study shows the feasibility of using DNA methylation profiling on FFPE and liquid biopsy samples such as blood, ascites, and pleural effusions in a fast and affordable way. Our novel RRBS-based technique requires minimal DNA input, can be performed in <1 week, and is highly adaptable to specific diagnostic problems as we only use 5 FFPE references per tumor entity. We believe that cfRRBS methylation profiling could be a valuable addition to the pathologist's toolbox in the diagnosis of CUPs.

Application of Transcriptome-Based Gene Set Featurization for Machine Learning Model to Predict the Origin of Metastatic Cancer.

Identifying the primary site of origin of metastatic cancer is vital for guiding treatment decisions, especially for patients with cancer of unknown primary (CUP). Despite advanced diagnostic techniques, CUP remains difficult to pinpoint and is responsible for a considerable number of cancer-related fatalities. Understanding its origin is crucial for effective management and potentially improving patient outcomes. This study introduces a machine learning framework, ONCOfind-AI, that leverages transcriptome-based gene set features to enhance the accuracy of predicting the origin of metastatic cancers. We demonstrate its potential to facilitate the integration of RNA sequencing and microarray data by using gene set scores for characterization of transcriptome profiles generated from different platforms. Integrating data from different platforms resulted in improved accuracy of machine learning models for predicting cancer origins. We validated our method using external data from clinical samples collected through the Kangbuk Samsung Medical Center and Gene Expression Omnibus. The external validation results demonstrate a top-1 accuracy ranging from 0.80 to 0.86, with a top-2 accuracy of 0.90. This study highlights that incorporating biological knowledge through curated gene sets can help to merge gene expression data from different platforms, thereby enhancing the compatibility needed to develop more effective machine learning prediction models.

Cancers of Unknown Primary Origin: Real-World Clinical Outcomes and Genomic Analysis at the European Institute of Oncology.

BACKGROUND: Cancer of unknown primary origin (CUP) poses a significant challenge due to poor clinical outcomes and limited treatment options. As such, further definition of clinicopathological factors and genomic profile to better adapt treatment strategies is required. METHODS: Medical records were interrogated to retrospectively include CUP with available clinical and genomics data at the European Institute of Oncology. Next-generation sequencing (NGS) included targeted panels. Statistical analyses were conducted with R Software 4.2.2. RESULTS: A total of 44 patients were included. With a median follow-up of 39.46 months (interquartile range [IQR] 35.98-47.41 months), median PFS (mPFS) to first-line regimen was 3.98 months (95% CI 3.22-5.98), with a clinical benefit rate of 26% (95% CI 14%-49%), and disease control rate (DCR) limited to 48.28%. Most patients (26 of 31, 83.87%) received platinum-doublet chemotherapy, with no statistically significant difference between first-line treatment regimens. Median OS (mOS) was 18.8 months (95% CI 12.3-39.9), with a 12-month OS rate of 66% (95% CI 50%-85%). All patients received comprehensive genomic profiling (CGP). For 11 patients, NGS was unsuccessful due to low sample quantity and/or quality. For the remaining, TP53 (n = 16, 48%) and KRAS (n = 10, 30%) represented the most altered (alt) genes. No microsatellite instability was observed (0 of 28), while 6 of 28 (21.43%) tumors carried high TMB (≥10 mutation per megabase). Eight of 33 tumors (24.2%) displayed at least one actionable alteration with potential clinical benefit according to ESCAT. Only 2 of them received targeted therapy matched to genomic alterations, with a combined mPFS of 2.63 months (95% CI 1.84-not evaluable) as third-line regimens. Six patients received anti-PD1/PD-L1 therapy, showing a meaningful mPFS of 13 months (95% CI 2.04-not evaluable). CONCLUSION: CUP exhibits poor prognosis with limited benefits from standard treatment regimens. A significant proportion of CUPs carry actionable alterations, underscoring the importance of genomic profiling to gather additional treatment opportunities. In addition, immunotherapy might represent a valuable treatment option for a subset of CUP. Finally, accurate definition of sequencing methods and platforms is crucial to overcome NGS failures.

Head and Neck Squamous Cell Carcinoma of Unknown Primary: A Diagnostic Work-Up.

The current work-up of the primary tumor site of a head and neck squamous cell carcinoma of unknown primary is not standardized and results in several time-consuming procedures that delay treatment initiation. This article seeks to consolidate contemporary strategies used to identify the primary tumor site of an unknown primary head and neck squamous cell carcinoma and offer recommendations based on current literature review.

Identifying the primary tumour in patients with cancer of unknown primary (CUP) using [18F]FDG PET/CT: a systematic review and individual patient data meta-analysis.

PURPOSE: In this systematic review and individual patient data (IPD) meta-analysis, we analysed the diagnostic performance of [18F]FDG PET/CT in detecting primary tumours in patients with CUP and evaluated whether the location of the predominant metastatic site influences the diagnostic performance. METHODS: A systematic literature search from January 2005 to February 2024 was performed to identify articles describing the diagnostic performance of [18F]FDG PET/CT for primary tumour detection in CUP. Individual patient data retrieved from original articles or obtained from corresponding authors were grouped by the predominant metastatic site. The diagnostic performance of [18F]FDG PET/CT in detecting the underlying primary tumour was compared between predominant metastatic sites. RESULTS: A total of 1865 patients from 32 studies were included. The largest subgroup included patients with predominant bone metastases (n = 622), followed by liver (n = 369), lymph node (n = 358), brain (n = 316), peritoneal (n = 70), lung (n = 67), and soft tissue (n = 23) metastases, leaving a small group of other/undefined metastases (n = 40). [18F]FDG PET/CT resulted in pooled detection rates to identify the primary tumour of 0.74 (for patients with predominant brain metastases), 0.54 (liver-predominant), 0.49 (bone-predominant), 0.46 (lung-predominant), 0.38 (peritoneal-predominant), 0.37 (lymph node-predominant), and 0.35 (soft-tissue-predominant). CONCLUSION: This individual patient data meta-analysis suggests that the ability of [18F]FDG PET/CT to identify the primary tumour in CUP depends on the distribution of metastatic sites. This finding emphasises the need for more tailored diagnostic approaches in different patient populations. In addition, alternative diagnostic tools, such as new PET tracers or whole-body (PET/)MRI, should be investigated.

Head and neck squamous cell carcinomas of unknown primary: Can ancillary studies help identify more primary tumor sites?

A subset of head and neck squamous cell carcinomas present solely as metastatic disease in the neck and are of unknown primary origin (SCCUP). Most primary tumors will ultimately be identified, usually in the oropharynx. In a minority of cases, the primary site remains elusive. Here, we examine the role of ancillary testing, including mutational signature analysis (MSA), to help identify likely primary sites in such cases. Twenty-two cases of SCCUP in the neck, collected over a 10-year period, were classified by morphology and viral status; including human papillomavirus (HPV) testing by p16 immunohistochemistry (IHC) and RT-qPCR, as well as Epstein-Barr virus (EBV) testing by EBER-ISH. CD5 and c-KIT (CD117) IHC was done to evaluate for possible thymic origin in all virus-negative cases. Whole exome sequencing, followed by MSA, was used to identify UV signature mutations indicative of cutaneous origin. HPV was identified in 12 of 22 tumors (54.5%), favoring an oropharyngeal origin, and closely associated with nonkeratinizing tumor morphology (Fisher's exact test; p = 0.0002). One tumor with indeterminant morphology had discordant HPV and p16 status (p16+/HPV-). All tumors were EBV-negative. Diffuse expression of CD5 and c-KIT was identified in 1 of 10 virus-negative SCCUPs (10%), suggesting a possible ectopic thymic origin rather than a metastasis. A UV mutational signature, indicating cutaneous origin, was identified in 1 of 10 (10%) virus-negative SCCUPs. A cutaneous auricular primary emerged 3 months after treatment in this patient. Primary tumors became clinically apparent in 2 others (1 hypopharynx, 1 hypopharynx/larynx). Thus, after follow-up, 6 tumors remained unclassifiable as to the possible site of origin (27%). Most SCCUPs of the neck in our series were HPV-associated and thus likely of oropharyngeal origin. UV signature mutation analysis and additional IHC for CD5 and c-KIT for possible thymic origin may aid in further classifying virus-negative unknown primaries. Close clinical inspection of hypopharyngeal mucosa may also be helpful, as a subset of primary tumors later emerged at this site.

A comparison of DNA sequencing and gene expression profiling to assist tissue of origin diagnosis in cancer of unknown primary.

Cancer of unknown primary (CUP) is a syndrome defined by clinical absence of a primary cancer after standardised investigations. Gene expression profiling (GEP) and DNA sequencing have been used to predict primary tissue of origin (TOO) in CUP and find molecularly guided treatments; however, a detailed comparison of the diagnostic yield from these two tests has not been described. Here, we compared the diagnostic utility of RNA and DNA tests in 215 CUP patients (82% received both tests) in a prospective Australian study. Based on retrospective assessment of clinicopathological data, 77% (166/215) of CUPs had insufficient evidence to support TOO diagnosis (clinicopathology unresolved). The remainder had either a latent primary diagnosis (10%) or clinicopathological evidence to support a likely TOO diagnosis (13%) (clinicopathology resolved). We applied a microarray (CUPGuide) or custom NanoString 18-class GEP test to 191 CUPs with an accuracy of 91.5% in known metastatic cancers for high-medium confidence predictions. Classification performance was similar in clinicopathology-resolved CUPs - 80% had high-medium predictions and 94% were concordant with pathology. Notably, only 56% of the clinicopathology-unresolved CUPs had high-medium confidence GEP predictions. Diagnostic DNA features were interrogated in 201 CUP tumours guided by the cancer type specificity of mutations observed across 22 cancer types from the AACR Project GENIE database (77,058 tumours) as well as mutational signatures (e.g. smoking). Among the clinicopathology-unresolved CUPs, mutations and mutational signatures provided additional diagnostic evidence in 31% of cases. GEP classification was useful in only 13% of cases and oncoviral detection in 4%. Among CUPs where genomics informed TOO, lung and biliary cancers were the most frequently identified types, while kidney tumours were another identifiable subset. In conclusion, DNA and RNA profiling supported an unconfirmed TOO diagnosis in one-third of CUPs otherwise unresolved by clinicopathology assessment alone. DNA mutation profiling was the more diagnostically informative assay. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

A machine learning-based method for feature reduction of methylation data for the classification of cancer tissue origin.

BACKGROUND: Genome DNA methylation profiling is a promising yet costly method for cancer classification, involving substantial data. We developed an ensemble learning model to identify cancer types using methylation profiles from a limited number of CpG sites. METHODS: Analyzing methylation data from 890 samples across 10 cancer types from the TCGA database, we utilized ANOVA and Gain Ratio to select the most significant CpG sites, then employed Gradient Boosting to reduce these to just 100 sites. RESULTS: This approach maintained high accuracy across multiple machine learning models, with classification accuracy rates between 87.7% and 93.5% for methods including Extreme Gradient Boosting, CatBoost, and Random Forest. This method effectively minimizes the number of features needed without losing performance, helping to classify primary organs and uncover subgroups within specific cancers like breast and lung. CONCLUSIONS: Using a gradient boosting feature selector shows potential for streamlining methylation-based cancer classification.

Indications for oropharyngeal biopsy in head and neck squamous cell carcinoma of unknown primary: A systematic review (HNSCCUP).

INTRODUCTION: Patients presenting with head and neck squamous cell carcinoma of unknown primary (HNSCCUP) remain challenging clinical scenarios as large variation exists in practices used to locate the primary. OBJECTIVE: The objective of this systematic review is to review of the literature and offer recommendations for oropharyngeal biopsies in HNSCCUP. METHOD: Pubmed, Medline and Embase were searched to identify studies from inception to October 2021. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines were followed. RESULTS: A total of 483 articles were included and screened, 41 studies met the inclusion criteria, including over 3400 patients from the original articles (122 of these patients were reported on in two sequential articles by a single author - table 1) and 4 large metaanalyses including 1852 patients. The primary site identification rate following random biopsies or deep tissue biopsies is less than 5% in most studies. The mean detection rate following ipsilateral tonsillectomy is 34%; two pooled analyses indicate that the mean detection rate following tongue base mucosectomy is 64%, with this figure rising when the tonsils are negative. CONCLUSIONS: High level evidence is lacking, with heterogeneity in the reported studies. Published meta-analyses are based on retrospective data. There is little evidence supporting the practice of random/non-directed oropharyngeal biopsies. Available evidence supports palatine tonsillectomy and tongue base mucosectomy compared to deep tissue biopsies.

Feasibility of Point-of-Care Genomic Profiling in the Diagnosis and Treatment of Cancer of Unknown Primary.

INTRODUCTION: Cancer of unknown primary remains a challenging clinical entity. Despite receiving empiric chemotherapy, median overall survival is approximately 6-12 months. Site-specific therapy based on molecular characterization has been shown to improve outcomes; however, feasibility outside of clinical trials, especially in community centers, is lacking. This study explores the application of rapid next-generation sequencing in defining cancer of unknown primary and to identify therapeutic biomarkers. METHODS: A retrospective chart review was performed by identifying pathological samples designated cancer of unknown primary. Next-generation sequencing testing was based on an automated workflow utilizing the Genexus integrated sequencer, validated for clinical use. Genomic profiling was further integrated within a routine immunohistochemistry service, with results reported directly by anatomic pathologists. RESULTS: Between October 2020 and October 2021, 578 solid tumor samples underwent genomic profiling. Among this cohort, 40 were selected based on an initial diagnosis of cancer of unknown primary. The median (range) age at diagnosis was 70 (42-85) and 23 (57%) were female. Genomic data were used to support a site-specific diagnosis in 6 patients (15%). Median turnaround time was 3 business days (IQR: 1-5). Most common alterations identified were KRAS (35%), CDKN2A (15%), TP53 (15%), and ERBB2 (12%). Actionable molecular targeted therapies were identified in 23 (57%) patients, including alterations in BRAF, CDKN2A, ERBB2, FGFR2, IDH1, and KRAS. Immunotherapy-sensitizing mismatch repair deficiency was identified in 1 patient. CONCLUSION: This study supports the adoption of rapid next-generation sequencing among patients with cancer of unknown primary. We also demonstrate the feasibility of integration of genomic profiling with diagnostic histopathology and immunohistochemistry in a community practice setting. Diagnostic algorithms incorporating genomic profiling to better define cancer of unknown primary should be considered for future study.

TOD-CUP: a gene expression rank-based majority vote algorithm for tissue origin diagnosis of cancers of unknown primary.

Gene expression profiling holds great potential as a new approach to histological diagnosis and precision medicine of cancers of unknown primary (CUP). Batch effects and different data types greatly decrease the predictive performance of biomarker-based algorithms, and few methods have been widely applied to identify tissue origin of CUP up to now. To address this problem and assist in more precise diagnosis, we have developed a gene expression rank-based majority vote algorithm for tissue origin diagnosis of CUP (TOD-CUP) of most common cancer types. Based on massive tissue-specific RNA-seq data sets (10 553) found in The Cancer Genome Atlas (TCGA), 538 feature genes (biomarkers) were selected based on their gene expression ranks and used to predict tissue types. The top scoring pairs (TSPs) classifier of the tumor type was optimized by the TCGA training samples. To test the prediction accuracy of our TOD-CUP algorithm, we analyzed (1) two microarray data sets (1029 Agilent and 2277 Affymetrix/Illumina chips) and found 91% and 94% prediction accuracy, respectively, (2) RNA-seq data from five cancer types derived from 141 public metastatic cancer tumor samples and achieved 94% accuracy and (3) a total of 25 clinical cancer samples (including 14 metastatic cancer samples) were able to classify 24/25 samples correctly (96.0% accuracy). Taken together, the TOD-CUP algorithm provides a powerful and robust means to accurately identify the tissue origin of 24 cancer types across different data platforms. To make the TOD-CUP algorithm easily accessible for clinical application, we established a Web-based server for tumor tissue origin diagnosis (http://ibi. zju.edu.cn/todcup/).

Risk factors for cancer of unknown primary: a literature review.

Cancer of Unknown Primary (CUP) is metastatic cancer with an unidentifiable primary tumour origin during life. It remains difficult to study the occurrence and aetiology of CUP. Hitherto, it is unclear whether risk factors are associated with CUP, yet identifying these factors could reveal whether CUP is a specific entity or a cluster of metastasised cancers from various primary tumour origins. Epidemiological studies on possible CUP risk factors were systematically searched in PubMed and Web of Science on February 1st, 2022. Studies, published before 2022, were included if they were observational human-based, provided relative risk estimates, and investigated possible CUP risk factors. A total of 5 case-control and 14 cohort studies were included. There appears to be an increased risk for smoking in relation to CUP. However, limited suggestive evidence was found to link alcohol consumption, diabetes mellitus, and family history of cancer as increased risks for CUP. No conclusive associations could be made for anthropometry, food intake (animal or plant-based), immunity disorders, lifestyle (overall), physical activity, or socioeconomic status and CUP risk. No other CUP risk factors have been studied. This review highlights smoking, alcohol consumption, diabetes mellitus and family history of cancer as CUP risk factors. Yet, there remains insufficient epidemiological evidence to conclude that CUP has its own specific risk factor profile.

Comprehensive analysis of cancer of unknown primary and recommendation of a histological and immunohistochemical diagnostic strategy from China.

BACKGROUND: Previous studies on cancer of unknown primary (CUP) mainly focus on treatment and prognosis in western populations and lacked clinical evaluation of different IHC markers, so this study aimed to evaluate characteristics of CUP and recommend a diagnostic strategy from a single center in China. METHODS AND RESULTS: Data of 625 patients with CUP were retrospectively collected and reviewed. The patients ranged in age from 20 to 91 years, with a female-to-male ratio of 1.3:1. The predominant histological type was poor or undifferentiated adenocarcinomas (308; 49.3%). The results of Canhelp-Origin molecular testing for the identification of the tissue of origin in 262 of 369 patients (71.0%) were considered predictable (similarity score > 45), with the most common predicted primary tumor site being the breast (57, 21.8%). Unpredictable molecular results correlated with more aggressive clinical parameters and poor survival. Thee positivity rates of several targeted antibodies (GATA3, GCDFP15, TTF1, Napsin A, and PAX8), based on the clinically predicted site, were lower than those reported for the corresponding primary tumors. Nonetheless, TRPS1 and INSM1 were reliable markers of predicted breast carcinoma (75.0%) and neuroendocrine tumors (83.3%), respectively. P16 expression, as well as HPV and EBER testing contributed significantly to the diagnosis of squamous cell carcinomas. Survival analysis revealed that older ages (> 57), ≥ 3 metastatic sites, non-squamous cell carcinomas, bone/liver/lung metastases, unpredictable molecular results, and palliative treatment correlated with poor overall survival. CONCLUSIONS: We recommend a CUP diagnostic strategy involving the use of targeted antibody panels as per histological findings that is potentially applicable in clinical practice. The markers TRPS1, INSM1, and P16 expression, as well as HPV and EBER testing are particularly valuable in this aspect. Molecular testing is also predictive of survival rates.

A qualitative study of patients with Cancer of Unknown Primary: Perceptions of communication, understanding of diagnosis and genomic testing, and information needs.

OBJECTIVE: Patients with Cancer of Unknown Primary (CUP) commonly report poor understanding of their illness and high levels of psychological distress. Despite the potential benefits to CUP patients, there is a paucity of research exploring the reasons behind poor understanding of a CUP diagnosis. The aim of this study was to understand patients' experiences of communication with doctors, their understanding of diagnosis and the role of genomic testing, as well as their information needs. METHODS: Semi-structured interviews explored CUP patients' perceptions of communication with their doctors, understanding of their illness, and their needs regarding medical information. Qualitative inductive thematic analysis of transcribed audio-recordings was employed. SETTING/PARTICIPANTS: Nineteen patients were recruited from within a prospective cohort study involving routine genomic testing of CUP patients. RESULTS: CUP patients had varied perceptions of communication with doctors as well as different levels of need, readiness, and capacity for information. Some patients felt well understood and supported by their doctors while others did not. Many patients reported feeling overwhelmed and shocked when receiving their cancer diagnosis and emphasized the importance of family support in receiving and understanding medical information. While patients understood the implications of genomic testing for treatment and diagnosis, few had a detailed understanding of genomic testing. CONCLUSIONS: Patients' experience of communication and understanding of CUP could be potentially improved by clinicians' assessment of the communication style preferred by each patient and their family and the development of online resources to meet their evolving information needs.

Dose planning study of proton versus photon radiotherapy for head and neck squamous cell carcinoma of unknown primary in the primary and recurrent setting.

BACKGROUND: Patients with head and neck squamous cell carcinoma of unknown primary (HNCUP) are often treated with extensive radiotherapy (RT). Frequently, the bilateral nodal clinical target volume (nCTV) and the volumes of suspected mucosal primary sites (mCTV) of the pharynx and larynx is irradiated. This treatment is effective but toxic. New data suggest that omission of the contralateral nCTV and mCTV, results in few recurrences. The present study explores photon versus proton therapy, in the primary and recurrent setting. MATERIAL AND METHODS: An analysis of twelve patients previously treated for HNCUP was performed. A fictitious recurrence was defined in patients treated for unilateral disease. Independently a volumetric arc photon plan and an intensity-modulated proton plan was made for all cases and scenarios. RESULTS: Compared to the standard bilateral treatment this study shows that limiting the target to unilateral nCTV leads to a significant decrease in dysphagia of 18% and 17% and xerostomia of 4.0% and 5% for photon and protons, respectively. Comparing photon RT directly to proton RT shows a small and often insignificant gain, using protons for both bilateral and unilateral targets. Focusing on re-irradiation, benefits from using protons in both the primary setting and at re-irradiation were limited. However, using protons for re-irradiation only leads to a decrease in the tissue volume receiving a specific dose outside the target overlapping region, e.g., V90Gymean was 31, 25, and 22 cm3 for photons-photons, photons-protons, and protons-protons, respectively. For V100Gy of the ipsilateral carotid artery, no differences were observed. CONCLUSION: Omitting contralateral nCTV irradiation and mCTV irradiation will significantly reduce toxicity. The accumulated high dose volumes can be minimised using protons for re-irradiation. However, the use of protons for primary treatment provides limited benefit in most patients.

Machine learning models predict the primary sites of head and neck squamous cell carcinoma metastases based on DNA methylation.

In head and neck squamous cell cancers (HNSCs) that present as metastases with an unknown primary (HNSC-CUPs), the identification of a primary tumor improves therapy options and increases patient survival. However, the currently available diagnostic methods are laborious and do not offer a sufficient detection rate. Predictive machine learning models based on DNA methylation profiles have recently emerged as a promising technique for tumor classification. We applied this technique to HNSC to develop a tool that can improve the diagnostic work-up for HNSC-CUPs. On a reference cohort of 405 primary HNSC samples, we developed four classifiers based on different machine learning models [random forest (RF), neural network (NN), elastic net penalized logistic regression (LOGREG), and support vector machine (SVM)] that predict the primary site of HNSC tumors from their DNA methylation profile. The classifiers achieved high classification accuracies (RF = 83%, NN = 88%, LOGREG = SVM = 89%) on an independent cohort of 64 HNSC metastases. Further, the NN, LOGREG, and SVM models significantly outperformed p16 status as a marker for an origin in the oropharynx. In conclusion, the DNA methylation profiles of HNSC metastases are characteristic for their primary sites, and the classifiers developed in this study, which are made available to the scientific community, can provide valuable information to guide the diagnostic work-up of HNSC-CUP. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.