Cancer of unknown primary site

Advancements in Diagnostics and Therapeutics for Cancer of Unknown Primary in the Era of Precision Medicine

Cancer of unknown primary (CUP), a set of histologically confirmed metastases that cannot be identified or traced back to its primary despite comprehensive investigations, accounts for 2-5% of all malignancies. CUP is the fourth leading cause of cancer-related deaths worldwide, with a median overall survival (OS) of 3-16 months. CUP has long been challenging to diagnose principally due to the occult properties of primary site. In the current era of molecular diagnostics, advancements in methodologies based on cytology, histology, gene expression profiling (GEP), and genomic and epigenomic analysis have greatly improved the diagnostic accuracy of CUP, surpassing 90%. Our center conducted the world's first phase III trial and demonstrated improved progression-free survival and favorable OS by GEP-guided site-specific treatment of CUP, setting the foundation of site-specific treatment in first-line management for CUP. In this review, we detailed the epidemiology, etiology, pathogenesis, as well as the histologic, genetic, and clinical characteristics of CUP. We also provided an overview of the advancements in the diagnostics and therapeutics of CUP over the past 50 years. Moving forward, we propose optimizing diagnostic modalities and exploring further-line treatment regimens as two focus areas for future studies on CUP.

Case Report: Personalized diagnosis and treatment strategies for three cases of cancer of unknown primary based on molecular testing techniques

Cancer of unknown primary (CUP) is a malignancy characterized by metastatic disease at diagnosis with an unidentified primary site, accounting for 3-5% of all cancers. Despite significant advancements in cancer diagnosis and treatment in recent years, CUP management has been challenging due to its complexity and heterogeneity; therefore, its prognosis remains poor. This report presents three cases of CUP. The first case involved a 59-year-old female whose abdominal metastatic cancer was identified to be originating from a primary cervical cancer using a 90-gene panel; the disease was controlled with targeted immunotherapy. The second case was a 56-year-old male with cervical lymph node metastatic cancer; genetic testing suggested renal cancer as the primary site, and dual-targeted therapy resulted in approximately 28% tumor reduction. The third case involved a 71-year-old female with subcutaneous metastatic cancer, which was confirmed by genetic profiling to be related to breast cancer; she achieved stable disease after chemotherapy. Diagnosis and treatment of these three CUP cases demonstrated that molecular testing could significantly improve treatment outcomes and extend patient survival. Precision medicine based on molecular detection has shown substantial value in identifying the primary site of CUP, developing personalized treatment plans, and managing the disease. However, treatment costs and patient compliance remain challenging, necessitating further research to optimize both diagnostic and therapeutic strategies.

Role of 18 FDG PET/CT in Detecting Primary Tumors in Patients with Carcinoma of Unknown Primary: Single-Center Cross-Sectional Study from 2017 to 2023 (Extension Study)

Background  Carcinoma of unknown primary (CUP) is a diverse group of cancers in which the primary tumor site remains occult despite detailed investigations. This is an extension of a published parent study with a smaller cohort, to further validate the published facts of detection efficiency of 18F-fluorodeoxyglucose positron emission tomography/computed tomography ( 18 FDG PET/CT) in patients with CUP over a larger sample from 2017 to 2023. Methods  Patients with CUP referred for 18 FDG PET/CT scan for detection of primary sites during the study period were recruited. 18 FDG PET/CT scan was acquired using a standardized protocol, and patients with suspected primary sites underwent biopsies. Scan findings and biopsy results were analyzed to find the detection rate, sensitivity, area under the curve (AUC), and positive predictive value (PPV). As no biopsy was performed in cases with negative scan, these cases were considered false negatives (FNs). Results  Total 230 patients with CUP were included with similar demographic trend (mean age: 58 ± 14 years; 63% male and 37% female; mean body mass index: 26.82 ± 5.4 kg/m 2 ); 138/230 (60 vs. 74% in parent study) patients were found to have a hypermetabolic focus suggestive of primary tumor sites and subjected to biopsy which turned out positive in 127/138 (true positive [TP]: 92 vs. 76% in parent study) and negative in 11/138 (true negative [TN]: 8 vs. 24% in parent study). Sensitivity and PPV of 18 FDG PET/CT were 58 and 92%, respectively (68 and 76%, respectively, in parent study). The remaining 92/230 (40%) patients with negative 18 FDG PET/CT for primary focus did not have biopsy. No significant demographic difference was seen in patients with TP and FN studies ( p  > 0.05). Receiver operating characteristics (ROC) curve revealed fair diagnostic strength of 18 FDG PET/CT for detecting unknown primary (AUC 0.710; p ≤ 0.05; standard error = 0.0167; confidence interval: 0.647-0.768; vs. nonsignificant in parent study). Conclusion  We conclude that this extension study with a larger cohort compared with the parent study has found a similar detection efficiency of 18 FDG PET/CT for identifying primary tumor in patients with CUP (58 vs. 57%) but with better PPV and sensitivity. Upfront use of 18 FDG PET/CT in CUP could preclude the use of many futile diagnostic procedures. Furthermore, the use of tumor-specific PET tracers, higher resolution scanners, and acquiring delayed images in patients with negative 18 FDG study could reduce FN results in patients with CUP.

Long-Term Survival after Treatment with Induction Therapy and Surgery for Mediastinal Carcinoma of Unknown Primary

INTRODUCTION

Carcinoma of unknown primary (CUP) is rarely located in the mediastinum. Most cases are revealed to be metastatic lymph node carcinoma, which carries a poor prognosis. The optimal treatment for CUP confined to the mediastinum is yet to be established, and the long-term outcome of induction therapy in combination with surgery for mediastinal CUP is unclear.

CASE PRESENTATION

A 46-year-old man with no history of malignancy was diagnosed with anterior mediastinal adenocarcinoma through biopsy. The patient underwent chemoradiation for the tumor, which was initially suspected as invasive T4 lung cancer. After a favorable response to presurgical therapy, the tumor was deemed more likely a mediastinal tumor, and it was completely resected simultaneously with the thymus, the partial left lung, and the partial left innominate vein. The tumor contained histologic features identifiable as a lymph node tissue and lacked any thymic tissue, which led to the final diagnosis as metastatic lymph node adenocarcinoma; however, its origin was unknown. No signs of recurrence were detected for 13 years after surgery.

CONCLUSIONS

Our case suggests that even patients with mediastinal CUP deemed an advanced disease can achieve long-term survival after undergoing induction therapy and definitive surgery.

Peritoneal carcinomatosis after lumboperitoneal shunt in a patient with a cancer of unknown primary site: Case report and review of the literature

Cancer of unknown primary site (CUP) often presents with atypical clinical behaviours that make identifying the primary tumour challenging. In this paper, we discuss the case of a patient with brain metastases from a CUP, which was ultimately diagnosed as pleomorphic carcinoma of the lung following autopsy. Clinically, the development of peritoneal carcinomatosis had reduced suspicion of a primary lung neoplasm, despite imaging tests initially suggesting this. However, the patient had previously undergone lumboperitoneal (LP) shunt insertion. The sequence of clinical events and autopsy findings strongly indicated that the LP shunt facilitated the metastatic spread. In addition to this case report, we provide a systematic review of the literature on the role of ventriculoperitoneal (VP) and LP shunts in the metastatic dissemination of tumours. Although the spread of primary brain tumours via VP or LP shunts is rare, albeit well-documented, this phenomenon has been reported only twice for secondary tumours.

Deep learning-based classifier for carcinoma of unknown primary using methylation quantitative trait loci

Cancer of unknown primary (CUP) constitutes between 2% and 5% of human malignancies and is among the most common causes of cancer death in the United States. Brain metastases are often the first clinical presentation of CUP; despite extensive pathological and imaging studies, 20%-45% of CUP are never assigned a primary site. DNA methylation array profiling is a reliable method for tumor classification but tumor-type-specific classifier development requires many reference samples. This is difficult to accomplish for CUP as many cases are never assigned a specific diagnosis. Recent studies identified subsets of methylation quantitative trait loci (mQTLs) unique to specific organs, which could help increase classifier accuracy while requiring fewer samples. We performed a retrospective genome-wide methylation analysis of 759 carcinoma samples from formalin-fixed paraffin-embedded tissue samples using Illumina EPIC array. Utilizing mQTL specific for breast, lung, ovarian/gynecologic, colon, kidney, or testis (BLOCKT) (185k total probes), we developed a deep learning-based methylation classifier that achieved 93.12% average accuracy and 93.04% average F1-score across a 10-fold validation for BLOCKT organs. Our findings indicate that our organ-based DNA methylation classifier can assist pathologists in identifying the site of origin, providing oncologists insight on a diagnosis to administer appropriate therapy, improving patient outcomes.

Solving unknown primary cancer with earlier diagnosis - the SUPER-ED trial: study protocol for a stepped-wedge cluster randomised controlled trial to support earlier diagnosis for people presenting with malignancy of undefined primary origin

BACKGROUND

People with malignancy of undefined primary origin (MUO) have a poor prognosis and may undergo a protracted diagnostic workup causing patient distress and high cancer related costs. Not having a primary diagnosis limits timely site-specific treatment and access to precision medicine. There is a need to improve the diagnostic process, and healthcare delivery and support for these patients. This trial aims to implement and evaluate an optimal model of care for people presenting with MUO to reduce time to diagnosis, improve patient experiences and reduce healthcare costs.

METHODS/DESIGN

This is a pragmatic stepped-wedge cluster randomised trial comparing a control phase of standard practice with an intervention phase. Patient inclusion criteria are: 1) age 18 years or older, 2) presenting with suspected metastatic malignancy without an obvious primary site on imaging, 3) clinically appropriate to undergo diagnostic work-up and 4) able to provide written or verbal consent. The intervention is a new model of care comprising four key components: standardised diagnostic workup, dedicated cancer care coordinators, virtual multidisciplinary meetings and a website resource for patients, carers and clinicians. The primary endpoint is the time to completion of minimum diagnostic workup. Secondary outcomes are whether the type of tumour is diagnosed, clinical trial participation, referral to palliative care, patient-reported physical, social and mental health, patient-reported understanding and uncertainty. Implementation outcomes include acceptability, feasibility, fidelity and adoption and health care use and costs. Intervention implementation will be supported using clinical leadership, education and reinforcement. Patients who consent to having their data collected will receive the model of care active at the site at the time of recruitment. Patients will complete a patient-reported outcomes questionnaire four months after study enrolment. A health economic analysis will be included. Across 15 hospitals, a total sample size of 240 is planned.

DISCUSSION

There is a lack of intervention research for people presenting with MUO. The stepped-wedge design seeks to mitigate the potential challenge of enrolling people with a poor prognosis and high symptom burden in trials. This research will generate important evidence with scalability for future research at trial completion.

TRIAL REGISTRATION

ACTRN12622001504707.

Case report: HPV related pelvic retroperitoneal squamous cell cancer of unknown primary presenting as ovary neoplasm

INTRODUCTION

Retroperitoneal tumors (RPTs) of the pelvis are rare and often present asymptomatically. We report a rare case of human papillomavirus (HPV)-related primary retroperitoneal squamous cell carcinoma (PRSCC) that was preoperatively misdiagnosed as adnexal cancer.

CASE PRESENTATION

A menopausal 59-year-old woman presented with right leg pain persisting for two months. Imaging revealed a heterogeneous lesion in the right adnexal area; however, the uterus and left ovary appeared normal. Laboratory tests showed slightly elevated levels of cancer 125 (CA 125) and squamous cell carcinoma (SCC) antigens. The patient underwent surgical staging for the suspected ovarian cancer. Intraoperatively, the bilateral adnexa and uterus appeared normal. A lesion identified in the right pelvic retroperitoneal cavity was resected and its pathological analysis revealed SCC and cervical intraepithelial neoplasia III (CIN III) and immunohistochemical expression of cyclin-dependent kinase inhibitor 2A (p16) in the cervix. HPV 16 was identified by a polymerase chain reaction (PCR). The patient chose not to undergo any additional postoperative treatment. Her leg pain disappeared the day after the procedure but recurred a year later. A new tumor was detected on computed tomography (CT) in the same area.

DISCUSSION

PRSCC is rare and can be misdiagnosed as a gynaecological neoplasm. HPV can migrate to the retroperitoneal space and act as a carcinogen in this location.

CONCLUSIONS

HPV infection may contribute to the development of PRSCC. Complete surgical resection, with adjuvant radiotherapy and chemotherapy, is a viable treatment approach.

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.

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.

Comparative analysis of the expression of р16, PD-L1 in squamous cell carcinoma of the oropharynx and CUP syndrome

Introduction. metastases in the absence of a primary tumor (cancer of unknown primary (Cup) syndrome) are diagnosed in 2–4 % of malignant tumor cases. This pathology is characterized by early metastatic dissemination, weak response to conventional chemotherapy, and aggressive progression. The use of checkpoint inhibitors targeting programmed cell death protein 1 (pD-1) and its ligand (pD-L1) has shown good results in treatment of various cancers including oropharyngeal squamous cell carcinoma (OpSCC). In Cup syndrome, the effectiveness of checkpoint inhibitors is rarely investigated, and pD-L1 expression is often not measured.Aim. To compare the frequency of p16 and pD-L1 hyperexpression in OpSCC and Cup syndrome, and to analyze dependency of survival rates on the level of expression of p16, the most important prognostic marker.Materials and methods. The study included 121 patients (59 with OpSCC and 62 with Cup syndrome) who received medical treatment in the multidisciplinary medical Center “medical City” (Tyumen) and Chelyabinsk Oncological Center of Oncology and Nuclear medicine between 2019 and 2023. Immunohistochemical examination was performed using the vENTANA Benchmark gX with primary antibodies against pD-L1 (clone Sp263, uSA) and р16 (uS Biological, uSA). Statistical analysis of the data was performed using SpSS 26 software. Long-term treatment outcomes were evaluated using 1-, 3-, 5-year survival rates and median survival. Overall survival was analyzed using the kaplan-meier method. Statistical significance of the differences was evaluated using the Cox model.Results. The studied groups did not differ by sex (p = 0.472), age (р = 0.640), and N stage (р = 0.262). patient age in the whole population varied between 42 and 81 years (median age 61.89 ± 11.9 years; mean age 60.81 ± 9.8 years). pD-L1 expression rate was higher in Cup syndrome at 92 % compared to 73 % in OpSCC (statistically significant difference; р = 0.01). Analysis of the association of ORSCC and Cup syndrome with human papilloma virus showed statistically significant difference in p16 hyperexpression: patients with OpSCC had p16-positive status more frequently (53 % of cases) while patients with Cup syndrome mostly had p16-negative status (73 % of cases). mean life expectancy of patients with OpSCC and p16-positive status was 62.65 months (95 % confidence interval 54.98–70.31), minimal observation period was 12 months, maximal was 70 months. mean life expectancy of patients with Cup syndrome and positive p16 status was 66.22 months (95 % confidence interval 56.35–76.10), minimal observation period was 12 months, maximal was 70 months. No statistically significant differences in survival rates of patients with OpSCC and Cup syndrome were found (р = 0.999).Conclusion. The study showed higher pD-L1 expression in patients with Cup syndrome compared to patients with OpSCC: 92 and 73 %, respectively (р = 0.01). The obtained results highlight the importance of routine pD-L1 expression evaluation in patients with Cup syndrome. The frequency of p16 hyperexpression was higher in OpSCC compared to Cup syndrome: 53 % versus 27 % (р = 0.02) which agrees with the worldwide epidemiological data: among all malignant neoplasms of the head and neck, Hpv infection is most common in OpSCC. Therefore, it serves as an important sign of hidden oropharyngeal cancer in Cup syndrome.

Exploring the molecular landscape of cancer of unknown primary: A comparative analysis with other metastatic cancers

Cancer of unknown primary (CUP) tumors are biologically very heterogeneous, which complicates stratification of patients for treatment. Consequently, these patients face limited treatment options and a poor prognosis. With this study, we aim to expand on the current knowledge of CUP biology by analyzing two cohorts: a well-characterized cohort of 44 CUP patients, and 213 metastatic patients with known primary. These cohorts were treated at the same institution and characterized by identical molecular assessments. Through comparative analysis of genomic and transcriptomic data, we found that CUP tumors were characterized by high expression of immune-related genes and pathways compared to other metastatic tumors. Moreover, CUP tumors uniformly demonstrated high levels of tumor-infiltrating leukocytes and circulating T cells, indicating a strong immune response. Finally, the genetic landscape of CUP tumors resembled that of other metastatic cancers and demonstrated mutations in established cancer genes. In conclusion, CUP tumors possess a distinct immunophenotype that distinguishes them from other metastatic cancers. These results may suggest an immune response in CUP that facilitates metastatic tumor growth while limiting growth of the primary tumor.

Poorly differentiated squamous cell carcinoma of unknown primary location a case report of perineal presentation

INTRODUCTION

Cancers of unknown primary origin (CUP) pose a significant clinical challenge, representing a small percentage (1 to 5 %) of overall cancer cases. The patient is a 31-year-old male who has been diagnosed with poorly differentiated infiltrating squamous cell carcinoma, which has been classified as CUP. The exceptional perineal presentation and diagnostic process serve as a reminder of the diverse nature of CUPs and the crucial role played by advanced imaging methods and a multidisciplinary approach. The inclusion of this case, the seventh one in the literature, deepens our understanding of CUPs.

PRESENTATION OF CASE

A 31-year-old man came in with a gradual onset of perineal pain that had been worsening for the past six months. A nodular lesion in the urogenital triangle, infiltrating the bulbo spongiosus muscle, was surgically removed. The histopathology results confirmed a poorly differentiated squamous cell carcinoma. Despite conducting extensive examinations, the multidisciplinary team was unable to determine the source of the tumour, classifying it as CUP. One year post-surgery, the patient remains in complete remission.

DISCUSSION

The management of CUPs can be challenging because of the variety of their origins and presentations. The importance of advanced imaging, pathological and biological techniques, as well as meticulous surgical intervention, is emphasized in this case, as it helps in avoiding unnecessary adjuvant therapies.

CONCLUSION

This case highlights the significance of a customized and interdisciplinary approach in effectively managing CUPs, especially when they present in unusual ways. Timely surgical intervention, backed by comprehensive imaging and pathological analysis, can result in positive results.

Seeing the primary tumor because of all the trees: Cancer type prediction on low-dimensional data

The Cancer of Unknown Primary (CUP) syndrome is characterized by identifiable metastases while the primary tumor remains hidden. In recent years, various data-driven approaches have been suggested to predict the location of the primary tumor (LOP) in CUP patients promising improved diagnosis and outcome. These LOP prediction approaches use high-dimensional input data like images or genetic data. However, leveraging such data is challenging, resource-intensive and therefore a potential translational barrier. Instead of using high-dimensional data, we analyzed the LOP prediction performance of low-dimensional data from routine medical care. With our findings, we show that such low-dimensional routine clinical information suffices as input data for tree-based LOP prediction models. The best model reached a mean Accuracy of 94% and a mean Matthews correlation coefficient (MCC) score of 0.92 in 10-fold nested cross-validation (NCV) when distinguishing four types of cancer. When considering eight types of cancer, this model achieved a mean Accuracy of 85% and a mean MCC score of 0.81. This is comparable to the performance achieved by approaches using high-dimensional input data. Additionally, the distribution pattern of metastases appears to be important information in predicting the LOP.

Genomic Catastrophe (Chromothripsis and Polyploidy) Correlates With Tumor Distribution in Extrauterine High-grade Serous Carcinoma

Most extrauterine high-grade serous carcinomas (HGSCs) are thought to develop first in the distal fallopian tube. Most models of HGSC assume origin from relatively stable, noninvasive serous tubal intraepithelial carcinomas. However, widespread tumor involvement in the absence of a serous tubal intraepithelial carcinoma could occur after catastrophic genomic events (CGEs; such as chromothripsis or polyploidy). Twenty-six HGSCs assigned to fallopian tube (n = 9, group 1) and/or ovary (n = 9, group 2), and primary peritoneal (n = 8, group 3) were assessed by microarray (Oncoscan). CGEs were identified in 15/26 (57.7%); chromothripsis-like pattern in 13/26 (50.0%) and polyploidy in 6/26 (23.1%). CGE was seen in 4/9 (44.4%), 9/9 (100%), and 2/8 (25%) cases in groups 1. 2, and 3, respectively. Overall, CGEs were seen in 9/9 (100%) cases with grossly evident ovarian parenchymal involvement versus 6/17 (35.3%) without ( P = 0.0024). Ovarian size (measured on the long axis) correlated with CGE positivity ( P = 0.016). CGEs are significantly more common in HGSCs with ovarian parenchymal involvement compared with those limited to the fallopian tube and/or extraovarian tissues. These associations suggest geographically different tumor growth patterns and support the subdivision of HGSCs according to not only the stage but also tumor distribution. They have implications for clinical and pathologic presentation, trajectory of tumor evolution, and in the case of primary peritoneal HGSCs, potentially unique precursors to tumor transitions that could inform or influence cancer prevention efforts.

Metastatic renal cell carcinoma with occult primary: a multicenter prospective cohort

Metastatic carcinoma of presumed renal origin (rCUP) has recently emerged as a new entity within the heterogeneous entity of Cancers of Unknown Primary (CUP) but their biological features and optimal therapeutic management remain unknown. We report the molecular characteristics and clinical outcome of a series of 25 rCUP prospectively identified within the French National Multidisciplinary Tumor Board for CUP. This cohort strongly suggests that rCUP share similarities with common RCC subtypes and benefit from renal-tailored systemic treatment. This study highlights the importance of integrating clinical and molecular data for optimal diagnosis and management of CUP.

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.

Programmed death-ligand 1 expression in carcinoma of unknown primary

We examined the expression of programmed death-ligand 1 (PD-L1) in carcinoma of unknown primary (CUP) and its potential implications. Tissue microarrays were constructed for 72 CUP cases (histologic subtypes: 22 adenocarcinoma, 15 poorly differentiated carcinoma, 19 squamous cell carcinoma, and 14 undifferentiated carcinoma; clinical subtype: favorable type 17 [23.6%], unfavorable type 55 [76.4%]), with immunohistochemical staining performed for PD-L1 (22C3, SP142, SP263, and 28 - 8), CK7, and CK20 to determine the association between staining results and clinicopathological parameters. In CUP, the PD-L1 positivity rate was 5.6-48.6% (tumor cells [TC] or tumor proportion score [TPS]: 5.6-36.1%, immune cell score [IC]: 8.3-48.6%, combined positive score [CPS]: 16.7%) using different cutoff values for 22C3 (TPS ≥ 1%, CPS ≥ 10), SP142 (TC ≥ 50%, IC ≥ 10%), SP263, and 28 - 8 (TC and IC ≥ 1%). PD-L1 SP142 TC and PD-L1 SP263 IC showed the lowest (5.6%) and highest (48.6%) positivity rates, respectively. The PD-L1 positivity rate did not significantly differ based on the histologic subtype, clinical subtype, or CK7/CK20 across clones. Considering TC κ ≥ 1%, TC κ ≥ 50%, IC κ ≥ 1%, and IC κ ≥ 10%, the PD-L1 positivity rate was TC = 4.2-36.1% and IC = 9.7-48.6%; the overall agreement between antibodies ranged from 69.4 to 93.1%, showing fair or better agreement (κ ≥ 0.21). In CUP, PD-L1 positivity varied depending on antibodies and scoring systems, with no difference observed according to histologic or clinical subtypes.

Prediction of tumor origin in cancers of unknown primary origin with cytology-based deep learning

Cancer of unknown primary (CUP) site poses diagnostic challenges due to its elusive nature. Many cases of CUP manifest as pleural and peritoneal serous effusions. Leveraging cytological images from 57,220 cases at four tertiary hospitals, we developed a deep-learning method for tumor origin differentiation using cytological histology (TORCH) that can identify malignancy and predict tumor origin in both hydrothorax and ascites. We examined its performance on three internal (n = 12,799) and two external (n = 14,538) testing sets. In both internal and external testing sets, TORCH achieved area under the receiver operating curve values ranging from 0.953 to 0.991 for cancer diagnosis and 0.953 to 0.979 for tumor origin localization. TORCH accurately predicted primary tumor origins, with a top-1 accuracy of 82.6% and top-3 accuracy of 98.9%. Compared with results derived from pathologists, TORCH showed better prediction efficacy (1.677 versus 1.265, P < 0.001), enhancing junior pathologists' diagnostic scores significantly (1.326 versus 1.101, P < 0.001). Patients with CUP whose initial treatment protocol was concordant with TORCH-predicted origins had better overall survival than those who were administrated discordant treatment (27 versus 17 months, P = 0.006). Our study underscores the potential of TORCH as a valuable ancillary tool in clinical practice, although further validation in randomized trials is warranted.

A case of pelvic squamous cell carcinoma of unknown primary origin that responded well to radiotherapy and nivolumab

Squamous cell carcinoma of unknown primary origin in the pelvis is rare. We report a case of a 64-year-old woman with a large osteolytic squamous cell carcinoma of unknown primary origin in the pelvis that presented with p16 expression. The patient presented with leg pain and swelling and was admitted to our hospital. Computed tomography scans of the pelvis revealed a large osteolytic tumor. A computed tomography-guided needle biopsy was performed, and pathological examination revealed neoplastic cells with metastatic squamous cell carcinoma presenting with p16 expression. Despite a whole-body examination, tumor origin remained undetected. The patient was treated for this metastatic squamous cell carcinoma of unknown primary using palliative radiotherapy for hip pain and nivolumab. Remarkable reduction in the tumor marker levels and tumor size were obtained after therapy. Finally, partial remission and progression-free survival for more than 7 months were achieved. In conclusion, we experienced a rare case with a large p16-positive squamous cell carcinoma of unknown primary in pelvis, which responded well to radiotherapy and nivolumab.

A case of laparoscopic lymphadenectomy for adenocarcinoma of unknown primary incidentally detected as a solitary enlarged lymph node along the common hepatic artery

BACKGROUND

Even in cancer of unknown primary (CUP), which is rare clinical condition, solitary anterosuperior lymph node (LN) along the common hepatic artery (No.8a LN) enlargement diagnosed as metastatic adenocarcinoma has never been reported.

CASE PRESENTATION

A 68-year-old Japanese male, with a history of early gastric cancer that had been completely treated by endoscopic submucosal dissection 26 years ago, was detected a single enlarged nodule along the common hepatic artery, No.8a LN, incidentally by computed tomography performed for monitoring of interstitial pneumonia. Endoscopic ultra-sound-guided fine needle aspiration revealed that this nodule was adenocarcinoma suggestive of metastasis, but other imaging studies, including upper and lower gastrointestinal endoscopy, positron emission tomography, and ultrasonography did not detect any primary cancer. We have finally diagnosed as the LN metastasis of CUP and performed laparoscopic lymphadenectomy for this tumor. The tumor was approximately 5 cm in size, was in close proximity to the pancreas, and involved part of the right gastric artery and vein. LNs in the No.5 and No.8a areas, including this tumor, were dissected laparoscopically, and radical resection was achieved. The patient had no postoperative complication and was discharged on postoperative day 10. Immunohistopathological findings revealed that the tumor was poorly differentiated adenocarcinoma, and different from the histology of gastric cancer resected 26 years ago, although the tumor was suggestive of gastrointestinal origin. Imaging studies performed 2 and 6 months after discharge also did not reveal a primary site.

CONCLUSION

We reported a case of solitary No.8a LN adenocarcinoma of CUP. For diagnostic and therapeutic purposes, radical resection is recommended for single enlarged intra-abdominal LN of CUP.

Cancer of unknown primary and the «seed and soil» hypothesis

The worldwide incidence rate of cancer of unknown primary (CUP) reaches 5% (Kang et al, 2021; Lee, Sanoff, 2020; Yang et al, 2022). CUP has an alarmingly high mortality rate, with 84% of patients succumbing within the first year following diagnosis (Registration and Service, 2018). Under normal circumstances, tumor cell metastasis follows the «seed and soil» hypothesis, displaying a tissue-specific pattern of cancer cell homing behavior based on the microenvironment composition of secondary organs. In this study, we questioned whether seed and soil concept applies to CUP, and whether the pattern of tumor and metastasis manifestations for cancer of known primary (CKP) can be used to inform diagnostic strategies for CUP. We compared data from metastatic and primary CUP foci to the metastasis patterns observed in CKP. Furthermore, we evaluated several techniques for identifying the tissue-of-origin (TOO) in CUP profiling, including DNA, RNA, and epigenetic TOO techniques.

Head and neck cancer of unknown primary: unveiling primary tumor sites through machine learning on DNA methylation profiles

BACKGROUND

The unknown tissue of origin in head and neck cancer of unknown primary (hnCUP) leads to invasive diagnostic procedures and unspecific and potentially inefficient treatment options for patients. The most common histologic subtype, squamous cell carcinoma, can stem from various tumor primary sites, including the oral cavity, oropharynx, larynx, head and neck skin, lungs, and esophagus. DNA methylation profiles are highly tissue-specific and have been successfully used to classify tissue origin. We therefore developed a support vector machine (SVM) classifier trained with publicly available DNA methylation profiles of commonly cervically metastasizing squamous cell carcinomas (n = 1103) in order to identify the primary tissue of origin of our own cohort of squamous cell hnCUP patient's samples (n = 28). Methylation analysis was performed with Infinium MethylationEPIC v1.0 BeadChip by Illumina.

RESULTS

The SVM algorithm achieved the highest overall accuracy of tested classifiers, with 87%. Squamous cell hnCUP samples on DNA methylation level resembled squamous cell carcinomas commonly metastasizing into cervical lymph nodes. The most frequently predicted cancer localization was the oral cavity in 11 cases (39%), followed by the oropharynx and larynx (both 7, 25%), skin (2, 7%), and esophagus (1, 4%). These frequencies concord with the expected distribution of lymph node metastases in epidemiological studies.

CONCLUSIONS

On DNA methylation level, hnCUP is comparable to primary tumor tissue cancer types that commonly metastasize to cervical lymph nodes. Our SVM-based classifier can accurately predict these cancers' tissues of origin and could significantly reduce the invasiveness of hnCUP diagnostics and enable a more precise therapy after clinical validation.

Dissemination of Circulating Tumor Cells in Breast and Prostate Cancer: Implications for Early Detection

Burgeoning evidence suggests that circulating tumor cells (CTCs) may disseminate into blood vessels at an early stage, seeding metastases in various cancers such as breast and prostate cancer. Simultaneously, the early-stage CTCs that settle in metastatic sites [termed disseminated tumor cells (DTCs)] can enter dormancy, marking a potential source of late recurrence and therapy resistance. Thus, the presence of these early CTCs poses risks to patients but also holds potential benefits for early detection and treatment and opportunities for possibly curative interventions. This review delves into the role of early DTCs in driving latent metastasis within breast and prostate cancer, emphasizing the importance of early CTC detection in these diseases. We further explore the correlation between early CTC detection and poor prognoses, which contribute significantly to increased cancer mortality. Consequently, the detection of CTCs at an early stage emerges as a critical imperative for enhancing clinical diagnostics and allowing for early interventions.

Advances in Cancer Research: Current and Future Diagnostic and Therapeutic Strategies

Cancers of unknown primary (CUP) exhibit significant cellular heterogeneity and malignancy, which poses significant challenges for diagnosis and treatment. Recent years have seen deeper insights into the imaging, pathology, and genetic characteristics of CUP, driven by interdisciplinary collaboration and the evolution of diagnostic and therapeutic strategies. However, due to their insidious onset, lack of evidence-based medicine, and limited clinical understanding, diagnosing and treating CUP remain a significant challenge. To inspire more creative and fantastic research, herein, we report and highlight recent advances in the diagnosis and therapeutic strategies of CUP. Specifically, we discuss advanced diagnostic technologies, including 12-deoxy-2-[fluorine-18]fluoro-D-glucose integrated with computed tomography (18F-FDG PET/CT) or 68Ga-FAPI (fibroblast activation protein inhibitor) PET/CT, liquid biopsy, molecular diagnostics, self-assembling nanotechnology, and artificial intelligence (AI). In particular, the discussion will extend to the effective treatment techniques currently available, such as targeted therapies, immunotherapies, and bio-nanotechnology-based therapeutics. Finally, a novel perspective on the challenges and directions for future CUP diagnostic and therapeutic strategies is discussed.

The practical utility of AI-assisted molecular profiling in the diagnosis and management of cancer of unknown primary: an updated review

Cancer of unknown primary (CUP) presents a complex diagnostic challenge, characterized by metastatic tumors of unknown tissue origin and a dismal prognosis. This review delves into the emerging significance of artificial intelligence (AI) and machine learning (ML) in transforming the landscape of CUP diagnosis, classification, and treatment. ML approaches, trained on extensive molecular profiling data, have shown promise in accurately predicting tissue of origin. Genomic profiling, encompassing driver mutations and copy number variations, plays a pivotal role in CUP diagnosis by providing insights into tumor type-specific oncogenic alterations. Mutational signatures (MS), reflecting somatic mutation patterns, offer further insights into CUP diagnosis. Known MS with established etiology, such as ultraviolet (UV) light-induced DNA damage and tobacco exposure, have been identified in cases of dedifferentiated/transdifferentiated melanoma and carcinoma. Deep learning models that integrate gene expression data and DNA methylation patterns offer insights into tissue lineage and tumor classification. In digital pathology, machine learning algorithms analyze whole-slide images to aid in CUP classification. Finally, precision oncology, guided by molecular profiling, offers targeted therapies independent of primary tissue identification. Clinical trials assigning CUP patients to molecularly guided therapies, including targetable alterations and tumor mutation burden as an immunotherapy biomarker, have resulted in improved overall survival in a subset of patients. In conclusion, AI- and ML-driven approaches are revolutionizing CUP management by enhancing diagnostic accuracy. Precision oncology utilizing enhanced molecular profiling facilitates the identification of targeted therapies that transcend the need to identify the tissue of origin, ultimately improving patient outcomes.

Bone metastatic cancer of unknown primary at initial presentation

INTRODUCTION

Cancer of unknown primary (CUP) is a challenging malignancy. The purpose of this study was to investigate the clinical characteristics and prognosis of bone metastatic CUP using the population-based Surveillance, Epidemiology, and End Results (SEER) database.

METHODS

From the SEER database, we identified 1908 patients with bone metastatic CUP at initial presentation between 2010 and 2018. Histology was subdivided following International Classification of Diseases for Oncology codes as Adenocarcinoma, Squamous cell, Neuroendocrine, or Carcinoma not otherwise specified (NOS). Cox proportional hazard modeling was applied using factors of age, sex, ethnicity, histological subtype, and therapeutic intervention.

RESULTS

Among the 1908 patients, histology was Neuroendocrine in 240 patients, Squamous cell in 201 patients, Adenocarcinoma in 810 patients and NOS in 657 patients. In each subtype, patients tended to be predominantly male and white. Chemotherapy was introduced for 28% of patients and radiation for 34% in the entire cohort. Survival in patients with bone metastatic CUP was unfavorable, with a median survival of 2 months. Among the histological subtypes, Adenocarcinoma showed shorter survival than the other groups. In addition, treatment interventions such as chemotherapy and radiation therapy prolonged survival, particularly for Squamous cell, Adenocarcinoma and NOS, but not for Neuroendocrine.

DISCUSSION

Bone metastatic CUP showed extremely poor prognosis, but treatment interventions such as chemotherapy and radiation generally offered survival benefits. Further randomized clinical research is needed to confirm the present results.

Biomarkers of systemic inflammation provide additional prognostic stratification in cancers of unknown primary

BACKGROUND

Biomarkers of systemic inflammation have been shown to predict outcomes in patients with cancer of unknown primary (CUP). We sought to validate these findings in patients with confirmed CUP (cCUP) and explore their role alongside existing clinicopathological prognostic categories.

PATIENTS AND METHODS

CUP oncologist from across the United Kingdom were invited to include patients with cCUP referred to their local CUP multidisciplinary team. Patient demographics, clinical, pathological and outcome data were recorded and analysed.

RESULTS

Data were available for 548 patients from four CUP services. 23% (n = 124) of patients met clinicopathological criteria for favourable-risk cCUP. On multivariate analysis c-reactive protein (CRP) (p < 0.001) and the Scottish Inflammatory Prognostic Score (SIPS: combining albumin and neutrophil count) (p < 0.001) were independently predictive of survival. CRP and SIPS effectively stratified survival in patients with both favourable-risk and poor-risk cCUP based on clinicopathological features.

CONCLUSIONS

Biomarkers of systemic inflammation are reliable prognostic factors in patients with cCUP, regardless of clinicopathological subgroup. We recommend that CRP or SIPS are incorporated into routine clinical assessments of patients with cCUP as a tool to aid investigation and/or treatment decision-making across all groups. Established clinicopathological factors can then be used to inform management pathways and specific systemic anticancer therapy selection.

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.

Differentiation of cancer of unknown primary and lymphoma in head and neck metastatic poorly differentiated cancer using 18 F-FDG PET/CT tumor metabolic heterogeneity index

OBJECTIVE

To explore the value of 18 F-FDG PET/CT tumor metabolic heterogeneity index (HI) and establish and validate a nomogram model for distinguishing head and neck cancer of unknown primary (HNCUP) from lymphoma with head and neck metastatic poorly differentiated cancer.

METHODS

This retrospective analysis was conducted on 1242 patients with cervical metastatic poorly differentiated cancer. 108 patients, who were clinically and pathologically confirmed as HNCUP or lymphoma, were finally enrolled. Two independent sample t-tests and χ 2 test were used to compare the clinical and imaging features. Binary logistic regression was used to screen for independent predictive factors.

RESULTS

Among the 108 patients), 65 patients were diagnosed with HNCUP and 43 were lymphoma. Gender ( P  = 0.001), SUV max ( P  < 0.001), SUV mean ( P  < 0.001), TLG ( P  = 0.012), and HI ( P  < 0.001) had statistical significance in distinguishing HNCUP and lymphoma. Female ( OR  = 4.546, P  = 0.003) and patients with HI ≥ 2.37 ( OR  = 3.461, P  = 0.047) were more likely to be diagnosed as lymphoma.

CONCLUSION

For patients with cervical metastatic poorly differentiated cancer, gender and HI were independent predictors of pathological type. For such patients, clinical attention should be paid to avoid misdiagnosing lymphoma as HNCUP, which may delay treatment.

Deciphering the origin and therapeutic targets of cancer of unknown primary: a case report that illustrates the power of integrative whole-exome and transcriptome sequencing analysis

Cancer of unknown primary (CUP) represents a significant diagnostic and therapeutic challenge, being the third to fourth leading cause of cancer death, despite advances in diagnostic tools. This article presents a successful approach using a novel genomic analysis in the evaluation and treatment of a CUP patient, leveraging whole-exome sequencing (WES) and RNA sequencing (RNA-seq). The patient, with a history of multiple primary tumors including urothelial cancer, exhibited a history of rapid progression on empirical chemotherapy. The application of our approach identified a molecular target, characterized the tumor expression profile and the tumor microenvironment, and analyzed the origin of the tumor, leading to a tailored treatment. This resulted in a substantial radiological response across all metastatic sites and the predicted primary site of the tumor. We argue that a comprehensive genomic and molecular profiling approach, like the BostonGene© Tumor Portrait, can provide a more definitive, personalized treatment strategy, overcoming the limitations of current predictive assays. This approach offers a potential solution to an unmet clinical need for a standardized approach in identifying the tumor origin for the effective management of 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.

Multiple-instance learning of somatic mutations for the classification of tumour type and the prediction of microsatellite status

Large-scale genomic data are well suited to analysis by deep learning algorithms. However, for many genomic datasets, labels are at the level of the sample rather than for individual genomic measures. Machine learning models leveraging these datasets generate predictions by using statically encoded measures that are then aggregated at the sample level. Here we show that a single weakly supervised end-to-end multiple-instance-learning model with multi-headed attention can be trained to encode and aggregate the local sequence context or genomic position of somatic mutations, hence allowing for the modelling of the importance of individual measures for sample-level classification and thus providing enhanced explainability. The model solves synthetic tasks that conventional models fail at, and achieves best-in-class performance for the classification of tumour type and for predicting microsatellite status. By improving the performance of tasks that require aggregate information from genomic datasets, multiple-instance deep learning may generate biological insight.

Cancer Diaspora of Undifferentiated Cancer

Undifferentiated cancer is a rapidly progressing cancer with poor prognosis. Sometimes, it is diagnosed at an advanced stage, and its origin is difficult to detect. A very unusual cancer was revealed by autopsy. The patient was an 83-year-old survivor of colon cancer, melanoma, and laryngeal cancer. He had been under watchful course observation after survival from laryngeal cancer but suddenly died due to aspiration pneumonia. The autopsy revealed undifferentiated cancer infiltrated the entire body, which was misdiagnosed with positron emission tomography (PET)/CT scan and MRI. The origin of this cancer was a mystery even with vigorous pathological evaluation. The patient was told that his previous cancers were all healed; however, undifferentiated cancer progressed rapidly to the entire body, just like "cancer diaspora". This report highlights the limit of diagnostic imaging tools for aggressive cancer, sounding the alarm for clinicians to look beyond old presumptions.

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features

Liver is one of the most common sites for metastases, which can occur on account of primary tumors from multiple sites of origin. Identifying the primary site of origin (PSO) of a metastasis can help in guiding therapeutic options for liver metastases. In this pilot study, we hypothesized that computer extracted handcrafted (HC) histomorphometric features can be utilized to identify the PSO of liver metastases. Cellular features, including tumor nuclei morphological and graph features as well as cytoplasm texture features, were extracted by computer algorithms from 175 slides (114 patients). The study comprised three experiments: (1) comparing and (2) fusing a machine learning (ML) model trained with HC pathomic features and deep learning (DL)-based classifiers to predict site of origin; (3) identifying the section of the primary tumor from which metastases were derived. For experiment 1, we divided the cohort into training sets composed of primary and matched liver metastases [60 patients, 121 whole slide images (WSIs)], and a hold-out validation set (54 patients, 54 WSIs) composed solely of liver metastases of known site of origin. Using the extracted HC features of the training set, a combination of supervised machine classifiers and unsupervised clustering was applied to identify the PSO. A random forest classifier achieved areas under the curve (AUCs) of 0.83, 0.64, 0.82, and 0.64 in classifying the metastatic tumor from colon, esophagus, breast, and pancreas on the validation set. The top features related to nuclear and peri-nuclear shape and textural attributes. We also trained a DL network to serve as a direct comparison to our method. The DL model achieved AUCs for colon: 0.94, esophagus: 0.66, breast: 0.79, and pancreas: 0.67 in identifying PSO. A decision fusion-based strategy was deployed to fuse the trained ML and DL classifiers and achieved slightly better results than ML or DL classifier alone (colon: 0.93, esophagus: 0.68, breast: 0.81, and pancreas: 0.69). For the third experiment, WSI-level attention maps were also generated using a trained DL network to generate a composite feature similarity heat map between paired primaries and their associated metastases. Our experiments revealed that epithelium-rich and moderately differentiated tumor regions of primary tumors were quantitatively similar to paired metastatic tumors. Our findings suggest that a combination of HC and DL features could potentially help identify the PSO for liver metastases while at the same time also potentially identify the spatial sites of origin for the metastases within primary tumors.

Prediction of Survival Prognosis for Spinal Metastasis From Cancer of Unknown Primary: Derivation and Validation of a Nomogram Model

STUDY DESIGN

Retrospective and prospective cohort study.

OBJECTIVES

Survival estimation is necessary in the decision-making process for treatment in patients with spinal metastasis from cancer of unknown primary (SMCUP). We aimed to develop a novel survival prediction system and compare its accuracy with that of existing survival models.

METHODS

A retrospective derivation cohort of 268 patients and a prospective validation cohort of 105 patients with SMCUP were performed. Univariate and multivariable survival analysis were used to generate independently prognostic variables. A nomogram model for survival prediction was established by integrating these independent predictors based on the size of the significant variables' β regression coefficient. Then, the model was subjected to bootstrap validation with calibration curves and concordance index (C-index). Finally, predictive accuracy was compared with Tomita, revised Tokuhashi and SORG score by the receiver-operating characteristic (ROC) curve.

RESULTS

The survival prediction model included six independent prognostic factors, including pathology (P < .001), visceral metastases (P < .001), Frankel score (P < .001), weight loss (P = .005), hemoglobin (P = .001) and serum tumor markers (P < .001). Calibration curve of the model showed good agreement between predicted and actual mortality risk in 6-, 12-, and 24-month estimation in derivation and validation cohorts. The C-index was .775 in the derivation cohort and .771 in the validation cohort. ROC curve analysis showed that the current model had the best accuracy for SMCUP survival estimation amongst 4 models.

CONCLUSIONS

The novel nomogram system can be applied in survival prediction for SMCUP patients, and furtherly be used to give individualized therapeutic suggestions based on patients' prognosis.

Connecting Agent-Based Models with High-Dimensional Parameter Spaces to Multidimensional Data Using SMoRe ParS: A Surrogate Modeling Approach

Across a broad range of disciplines, agent-based models (ABMs) are increasingly utilized for replicating, predicting, and understanding complex systems and their emergent behavior. In the biological and biomedical sciences, researchers employ ABMs to elucidate complex cellular and molecular interactions across multiple scales under varying conditions. Data generated at these multiple scales, however, presents a computational challenge for robust analysis with ABMs. Indeed, calibrating ABMs remains an open topic of research due to their own high-dimensional parameter spaces. In response to these challenges, we extend and validate our novel methodology, Surrogate Modeling for Reconstructing Parameter Surfaces (SMoRe ParS), arriving at a computationally efficient framework for connecting high dimensional ABM parameter spaces with multidimensional data. Specifically, we modify SMoRe ParS to initially confine high dimensional ABM parameter spaces using unidimensional data, namely, single time-course information of in vitro cancer cell growth assays. Subsequently, we broaden the scope of our approach to encompass more complex ABMs and constrain parameter spaces using multidimensional data. We explore this extension with in vitro cancer cell inhibition assays involving the chemotherapeutic agent oxaliplatin. For each scenario, we validate and evaluate the effectiveness of our approach by comparing how well ABM simulations match the experimental data when using SMoRe ParS-inferred parameters versus parameters inferred by a commonly used direct method. In so doing, we show that our approach of using an explicitly formulated surrogate model as an interlocutor between the ABM and the experimental data effectively calibrates the ABM parameter space to multidimensional data. Our method thus provides a robust and scalable strategy for leveraging multidimensional data to inform multiscale ABMs and explore the uncertainty in their parameters.

Diagnostics of Thyroid Cancer Using Machine Learning and Metabolomics

The objective of this research is, with the analysis of existing data of thyroid cancer (TC) metabolites, to develop a machine-learning model that can diagnose TC using metabolite biomarkers. Through data mining, pathway analysis, and machine learning (ML), the model was developed. We identified seven metabolic pathways related to TC: Pyrimidine metabolism, Tyrosine metabolism, Glycine, serine, and threonine metabolism, Pantothenate and CoA biosynthesis, Arginine biosynthesis, Phenylalanine metabolism, and Phenylalanine, tyrosine, and tryptophan biosynthesis. The ML classifications' accuracies were confirmed through 10-fold cross validation, and the most accurate classification was 87.30%. The metabolic pathways identified in relation to TC and the changes within such pathways can contribute to more pattern recognition for diagnostics of TC patients and assistance with TC screening. With independent testing, the model's accuracy for other unique TC metabolites was 92.31%. The results also point to a possibility for the development of using ML methods for TC diagnostics and further applications of ML in general cancer-related metabolite analysis.

Determinants Affecting the Clinical Implementation of a Molecularly Informed Molecular Tumor Board Recommendation: Experience from a Tertiary Cancer Center

Molecular Tumor Boards (MTBs) converge state-of-the-art next-generation sequencing (NGS) methods with the expertise of an interdisciplinary team consisting of clinicians, pathologists, human geneticists, and molecular biologists to provide molecularly informed guidance in clinical decision making to the treating physician. In the present study, we particularly focused on elucidating the factors impacting on the clinical translation of MTB recommendations, utilizing data generated from gene panel mediated comprehensive genomic profiling (CGP) of 554 patients at the MTB of the Comprehensive Cancer Center Erlangen, Germany, during the years 2016 to 2020. A subgroup analysis of cases with available follow-up data (n = 332) revealed 139 cases with a molecularly informed MTB recommendation, which was successfully implemented in the clinic in 44 (31.7%) of these cases. Here, the molecularly matched treatment was applied in 45.4% (n = 20/44) of cases for ≥6 months and in 25% (n = 11/44) of cases for 12 months or longer (median time to treatment failure, TTF: 5 months, min: 1 month, max: 38 months, ongoing at data cut-off). In general, recommendations were preferentially implemented in the clinic when of high (i.e., tier 1) clinical evidence level. In particular, this was the case for MTB recommendations suggesting the application of PARP, PIK3CA, and IDH1/2 inhibitors. The main reason for non-compliance to the MTB recommendation was either the application of non-matched treatment modalities (n = 30)/stable disease (n = 7), or deteriorating patient condition (n = 22)/death of patient (n = 9). In summary, this study provides an insight into the factors affecting the clinical implementation of molecularly informed MTB recommendations, and careful considerations of these factors may guide future processes of clinical decision making.

Pathological Fracture of the Proximal Humerus Occurred on Metastases of Probable Kidney Origin in the Absence of Primary Lesions: A Case Report

Cancer of unknown primary (CUP) origin represents a diagnostic and therapeutic challenge. These tumours spread to different parts of the body even if the site of origin has not been identified. When renal metastases are observed without an obvious primary lesion, it is important to exclude the possibility of a primary kidney tumour that may be unknown or too small to be detected. The diagnosis of CUP is established after a careful clinical evaluation and diagnostic tests, including blood chemistry and laboratory tests, instrumental exams (CT, MRI, PET, bone scan), biopsy, and molecular and cytogenetic analysis. Once the diagnosis of CUP with kidney metastases is confirmed, treatment depends on the location of the metastases, the patient's health status, and available treatment options. The latter includes surgery to remove metastases, radiation therapy, or systemic treatment such as chemotherapy or immunotherapy. It is important that patients with CUP are evaluated by a multidisciplinary team of specialists, who can contribute to planning the most appropriate treatment. In this article, we report the clinical case of a patient with a pathological fracture of the proximal humerus which occurred on metastases of probable renal origin in the absence of primary lesions.

Patient characteristics associated with definitive diagnosis of metastatic pancreatic cancer in those initially diagnosed with cancer of unknown primary

Cancer of unknown primary (CUP) and pancreatic cancer (PC) are malignancies associated with poor prognosis. CUP is the fourth most common cause of cancer mortality in the US, and median survival time is 3-4 months. PC is the third most common cause of cancer mortality in the US, and median survival time for patients with stage 3 or 4 PC is 2-3 months. The present study aimed to understand the patient characteristics of those initially misdiagnosed with CUP who ultimately received a diagnosis of PC. The present study used 2010-2015 Surveillance, Epidemiology, and End Results-Medicare data, a US population-based cancer registry linked to Medicare health insurance claims. Odds ratios (ORs) and 95% confidence intervals were calculated using two binary logistic regression models to compare the characteristics of patients who received definitive diagnosis between the CUP-PC group (those with an initial diagnosis of CUP who eventually received a stage 3 or 4 PC diagnosis) and the PC group (those diagnosed with stage 3 or 4 PC only). Approximately 26% of patients who received a definitive diagnosis of metastatic PC started with an initial diagnosis of CUP (n=17,565). The odds of definitive PC diagnosis in patients with CUP were lower for those with a comorbidity score of 0 [OR, 0.85 (95% CI: 0.79, 0.91)] and epithelial/unspecified histology [OR, 0.76 (95% CI: 0.71, 0.82)]. The odds of definitive PC diagnosis in patients with CUP were higher for patients of other race [OR, 1.27 (95% CI: 1.13, 1.43)] compared with white patients. Definitive diagnosis of PC in patients with CUP was lower in patients who were older with fewer or no comorbidities and unspecified histology. The complexity of CUP diagnosis and patient performance status may influence delays in diagnosis to a known primary site.

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.

Cancer of unknown primary histologically, genetically and spatially diagnosed as left ovary‑derived cancer: A case report

Cancer of unknown primary (CUP) is a heterogeneous syndrome of metastatic cancer in which the primary site cannot be determined even after a standard and comprehensive search. The present report describes a case in which the spatial distribution of the lymph node metastases contributed to the identification of the primary site. While the standard workup did not identify the primary tumor, genomic profiling analysis was useful in therapeutic management. A 68-year-old woman presented with a cancerous pleural effusion (adenocarcinoma). The primary site could not be identified, and the pleural effusion resolved spontaneously. After 11 months, the patient had elevated Krebs von den Lungen-6 and cancer antigen 125 levels, and multiple enlarged lymph nodes. Pathological diagnosis based on a biopsy sample of the para-aortic lymph nodes indicated that the tumor was a high-grade serous carcinoma of possible gynecological organ origin. The patient underwent surgery, including hysterectomy, bisalpingo-oophorectomy and lymph node dissection. Although there were no primary sites in the gynecological organs, marked lymphovascular invasion was found around the left ovary, suggesting a left ovary-derived tumor. Genetic testing revealed a high loss of heterozygosity score and high tumor mutational burden (TMB). The patient received paclitaxel and carboplatin therapy followed by a poly ADP-ribose polymerase inhibitor as regimens for ovarian cancer and achieved complete remission. The unique course of the disappearance of the effusion and the absence of tumor in the adnexa might be associated with the high immunogenicity of the tumor characterized by the high TMB. This case may provide insights into the pathogenesis of CUP.

Significance of Distinct Liquid Biopsy Compartments in Evaluating Somatic Mutations for Targeted Therapy Selection in Cancer of Unknown Primary

PURPOSE

Cancer of unknown primary (CUP) accounts for 2-5% of all cancer diagnoses, wherein standard investigations fail to reveal the original tumor site. Basket trials allocate targeted therapeutics based on actionable somatic mutations, independent of tumor entity. These trials, however, mostly rely on variants identified in tissue biopsies. Since liquid biopsies (LB) represent the overall tumor genomic landscape, they may provide an ideal diagnostic source in CUP patients. To identify the most informative liquid biopsy compartment, we compared the utility of genomic variant analysis for therapy stratification in two LB compartments (circulating cell-free (cf) and extracellular vesicle (ev) DNA).

METHODS

CfDNA and evDNA from 23 CUP patients were analyzed using a targeted gene panel covering 151 genes. Identified genetic variants were interpreted regarding diagnostic and therapeutic relevance using the MetaKB knowledgebase.

RESULTS

LB revealed a total of 22 somatic mutations in evDNA and/or cfDNA in 11/23 patients. Out of the 22 identified somatic variants, 14 are classified as Tier I druggable somatic variants. Comparison of variants identified in evDNA and cfDNA revealed an overlap of 58% of somatic variants in both LB compartments, whereas over 40% of variants were only found in one or the other compartment.

CONCLUSION

We observed substantial overlap between somatic variants identified in evDNA and cfDNA of CUP patients. Nonetheless, interrogation of both LB compartments can potentially increase the rate of druggable alterations, stressing the significance of liquid biopsies for possible primary-independent basket and umbrella trial inclusion.

Management and prognosis of patients with cancer of unknown primary: 20 years of experience

Background/aim

Cancer of unknown primary (CUP) is a difficult clinical entity to manage. The aim of the study was to investigate the sociodemographic and pathological characteristics, treatment options, and factors affecting overall survival (OS) in CUP patients whose primary tumor was not detected during follow-up.

Materials and methods

A total of 243 CUP patients whose primary tumors could not be detected during follow-up were included in the study. Their demographic characteristics, survival outcomes, and prognostic factors were investigated.

Results

Of the 243 patients included in this study, 61.7% were male and 38.3% were female, and the median age was 61 (range: 19-90) years. The most common histological type was adenocarcinoma (79%). The median follow-up time of the patients was 30.3 months (95% CI: 11.4-49.3), the median OS time was 9.1 months (95% CI: 7.2-11.0), and 72.4% of the patients received at least 1 line of chemotherapy (CT). The difference in survival between the patients who did and did not receive CT was statistically significant (median OS: 10.1 vs. 4.2 months, p = 0.003). According to the multivariate analysis, the presence of cholestasis (HR: 0.48, 95% CI: 0.29-0.79, p = 0.004), lung metastasis (HR: 0.69, 95% CI: 0.51-0.95, p = 0.001), second-line chemotherapy (HR: 1.69, 95% CI: 1.14-2.49, p < 0.001), and Eastern Cooperative Oncology Group (ECOG) performance status (HR: 0.20, 95% CI: 0.10-0.40, p < 0.001) were independent prognostic factors influencing OS.

Conclusion

CUP patients who receive multiple lines of chemotherapy tend to have longer survival. This is the first study to report cholestasis as a prognostic factor in CUP patients. In addition, the presence of lung metastases, not receiving second-line chemotherapy, and ECOG performance status (≥2) were found to be independent poor prognostic factors.

A SEER database retrospective cohort of 547 patients with penile non-squamous cell carcinoma: demographics, clinical characteristics, and outcomes

Introduction

Little research has investigated the prevalence and distribution of the diverse pathologies of non-squamous cell carcinoma (non-SCC) of the penis. Although rare in clinical practice, these cancers have become a focus of greater importance among patients, clinicians, and researchers, particularly in developing countries. The principal objective of this study was to analyze the major types of penile non-SCC, elucidate common treatment pathways, and highlight outcomes including 5-year survival.

Materials/methods

The Surveillance, Epidemiology, and End Results (SEER) database was queried between 2000 and 2018 to identify a retrospective cohort of patients with penile non-SCC. Demographic information, cancer characteristics, diagnostic methods, treatments administered, and survival were investigated.

Results

A total of 547 cases of penile non-SCC were included in the analysis. The most prevalent non-SCC cancers included epithelial neoplasms, not otherwise specified (NOS) (15.4%), unspecified neoplasms (15.2%), basal cell neoplasms (13.9%), blood vessel tumors (13.0%), nevi and melanomas (11.7%), and ductal and lobular neoplasms (9.9%). Over half (56.7%) of patients elected to undergo surgical intervention. Patients rarely received systemic therapy (3.8%) or radiation (4.0%). Five-year survival was 35.5%. Patients who underwent surgery had greater annual survival for 0-10 years compared to those who did not have surgery. Significant differences in survival were found between patients who had regional, localized, and distant metastases (p < 0.05). A significant difference in survival was found for patients married at diagnosis versus those who were unmarried at diagnosis (p < 0.05). Lower survival rates were observed for patients older than 70 years.

Discussion

Although less prevalent than SCC, penile non-SCC encompasses a diverse set of neoplasms. Patients in this cohort had a high utilization of surgical management leading to superior outcomes compared to those not receiving surgery. Radiation is an uncommonly pursued treatment pathway. Patient demographics and socioeconomic variables such as marital status may be valuable when investigating cancer outcomes. This updated database analysis can help inform diagnosis, management, and clinical outcomes for this rare group of malignancies.

Circulating microRNA Panels for Detection of Liver Cancers and Liver-Metastasizing Primary Cancers

Malignant liver tumors, including primary malignant liver tumors and liver metastases, are among the most frequent malignancies worldwide. The disease carries a poor prognosis and poor overall survival, particularly in cases involving liver metastases. Consequently, the early detection and precise differentiation of malignant liver tumors are of paramount importance for making informed decisions regarding patient treatment. Significant research efforts are currently directed towards the development of diagnostic tools for different types of cancer using minimally invasive techniques. A prominent area of focus within this research is the evaluation of circulating microRNA, for which dysregulated expression is well documented in different cancers. Combining microRNAs in panels using serum or plasma samples derived from blood holds great promise for better sensitivity and specificity for detection of certain types of cancer.