Rare Cancer Research Articles (Page 1)

To estimate the number of cancer-related deaths that could be attributed to spatial disparities in survival. Cohort study of cancer registry data. Australia, 1 January 2010 to 31 December 2019. The numbers and percentages of cancer-related deaths attributable to spatial disparities in survival were estimated by calculating the numbers of cancer-related deaths that would have occurred if all areas in Australia met or exceeded a benchmark 5-year survival rate. This benchmark corresponded to the survival rate of the area with survival better than 80% of all areas, with "area" referring to residential location at diagnosis. Of all 289 075 cancer-related deaths in Australia in 2010-2019, 33 892 (11.7%) were attributable to spatial disparities in survival. Although numbers were greatest in major cities, as remoteness and area disadvantage increased, the percentages of cancer-related deaths attributable to spatial disparities in survival increased. Of all cancer-related deaths in remote areas and the most socio-economically disadvantaged areas, 1569 of 5208 (30.1%) and 13 469 of 66 775 (20.2%) deaths were attributable to survival disparities, respectively. The highest numbers and percentages of attributable cancer deaths in remote areas were for rare cancers (529/1809 [29.3%]), lung cancer (300/1298 [23.1%]) and head and neck cancers (162/370 [43.8%]). In the most disadvantaged areas, rare cancers (3070/20 512 [15.0%]) and lung cancer (2640/18 057 [14.6%]) had the highest numbers of attributable cancer deaths. These findings quantify the impact of spatial disparities in survival and highlight the need for equitable access to diagnostic and treatment services across Australia.

Background Due to their rarity and complexity sarcomas require specialized multidisciplinary team management. COVID-19 pandemic brought to a rapid implementation of telemedicine and activation of digital tools. This study evaluates the perception of virtual disease multidisciplinary team among healthcare professionals of an European rare cancer referral center. Methods An online survey was administered to the participants of Regina Elena National Cancer Institute’s Sarcoma disease multidisciplinary team meetings held between 2020 and 2022. It was composed of 40 questions comparing face-to-face and virtual meetings. Data from the Institutional disease multidisciplinary team from 2019 to 2022 were also analyzed retrospectively to compare the pre-covid, covid, and post-covid phases. Results Twenty-two healthcare professionals answered the survey. In their opinion, decision-making process was not affected by virtual modality (86.0%). Regarding virtual meetings 90.0% were highly/moderately satisfied with depth of discussion, 95.0%–100% were able to interact adequately and access all relevant data. The most important improvements of virtual disease multidisciplinary team were better quality of clinical approach/research (22.7%–31.8%), technological innovations (50.0%), and logistical setting (95.5%). 90.0% to 100% thought that virtual disease multidisciplinary team could be approved thereafter. We observed an increase in participation rate from 58.0, to 62.0%, to 64.0% ( p = 0.0159) and a rise in the new cases discussed at meetings compared to the re-discussed ones from 30.1% to 37.9% to 42.3% ( p < 0.0001) in the pre-covid, covid, and post-covid phases, respectively. Conclusion Virtual disease multidisciplinary team enhances participation and discussion quality without compromising patient care.

Health literacy (HL) has been found to affect perceived information provision (PIP), satisfaction with information provision, and health-related quality of life (HRQoL) in patients with cancer. Patients with a rare cancer are confronted with challenges, such as a lack of information. The aim of this study was to explore the impact of HL on PIP, satisfaction with information provision, and on HRQoL in rare compared to common cancer patients.A population-based study was conducted using the PROFILES registry. Patients with rare (n = 385) and common (n = 1,692) cancer were included. Within group associations (low/medium HL, high HL, rare cancer, common cancer) were assessed. Regression analyses were used to assess associations between HL, PIP, satisfaction, and HRQoL, taking cancer group into account.Within the low/medium HL group, no statistically significant differences were found between rare and common cancer patients. Yet, within the high HL group, rare cancer patients scored significantly lower on all PIP-categories (except PIP-medical tests), satisfaction and HRQoL. Within the rare cancer group, patients with low/medium HL scored lower, compared to those with high HL, on PIP-medical tests and PIP-treatment, while within the common cancer group, patients with low/medium HL scored lower on all PIP-categories, satisfaction and HRQoL (all: p<0.05).Information needs might vary between patients with a different HL level and/or cancer group. Healthcare professionals should take individual needs into account, with a special focus on patients with a rare cancer and low/medium HL, in order to convey information in an understandable, patient-tailored way.

The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning. However, translating these advancements to address complex clinical challenges at the patient and slide level remains constrained by limited clinical data in disease-specific cohorts, especially for rare clinical conditions. We propose Transformer-based pathology Image and Text Alignment Network (TITAN), a multimodal whole-slide foundation model pretrained using 335,645 whole-slide images via visual self-supervised learning and vision-language alignment with corresponding pathology reports and 423,122 synthetic captions generated from a multimodal generative AI copilot for pathology. Without any fine-tuning or requiring clinical labels, TITAN can extract general-purpose slide representations and generate pathology reports that generalize to resource-limited clinical scenarios such as rare disease retrieval and cancer prognosis. We evaluate TITAN on diverse clinical tasks and find that it outperforms both ROI and slide foundation models across machine learning settings, including linear probing, few-shot and zero-shot classification, rare cancer retrieval, cross-modal retrieval and pathology report generation.

Gulf Cooperation Council (GCC) countries are undergoing a critical transformation in their healthcare systems. This empowers them to address the rising burden of complex diseases, including rare diseases, cancer, neurological disorders, and immunological illnesses, which involve a high cost of therapy. A strategic shift from volume- to value-based healthcare (VBH) emphasizes sustainability, enhanced accessibility, and improved health outcomes through innovation. GCC’s healthcare is marked by universal coverage and a shifting landscape of public-private partnerships. Rising pharmaceutical costs, especially for specialty drugs, continue to challenge budget sustainability. VBH offers a strategy to align healthcare expenditure with patient outcomes. This framework is supported by global and regional models such as managed entry agreements (MEAs), multi-criteria decision analysis, and real-world evidence (RWE). These models provide guidance for reimbursement strategies and support decision-making regarding high-value treatments. The GCC nations are also progressing towards policy discussion, but face challenges related to infrastructure, regulation, and workforce capacity. The Department of Health (DOH) in Abu Dhabi, which is a governmental health authority in the United Arab Emirates, has officially established a dedicated HTA unit to evaluate and assess new health technologies for evidence-informed decision making. This review highlights specialty care priorities and proposes target strategies such as expanding genetic databases, implementing screening programs, and establishing risk-sharing agreements to improve affordability, particularly for rare diseases. A consensus-driven phased roadmap for GCC-wide VBH adoption is recommended. This includes a focus on MEAs and patient-reported outcome measures, mid-term harmonization of health technology assessments (HTA) and RWE development as well as long-term establishment of digital ecosystems and value-based pricing platforms. Equitable and collaborative policies will be essential to achieving sustainable and inclusive healthcare systems across the GCC.

We present a label-free imaging flow cytometry system that integrates a microfluidic chip, imaged by a motion-sensitive (event-based) camera and an interferometric phase microscopy module using a simple frame-based camera. The event camera captures activity from the flowing cells, corresponding to thousands of frames per second, and triggers the significantly slower interferometric camera when a rare cell, requiring more sensitive analysis, is detected via a single raw-interferogram analysis, significantly reducing data volume. The raw interferometric data serves as an input to a deep neural network for rare-cell classification. We demonstrate the use of this system to detect and grade rare cancer cells in blood, where the event camera is used to rapidly classify between the common white blood cells and the rare cancer cells, and the interferometric camera is used to grade the cancer cell type (primary/metastatic), as a human model for detecting and grading circulating tumor cells in liquid biopsies. This hybrid approach enables efficient data acquisition, rapid processing, and high sensitivity, significantly reducing computational load, and is expected to find various applications in detecting and processing rare cells in imaging flow cytometry.

Clinical case reports in oncology are an untapped resource of patient data that include relationships between molecular alterations, tumor types, and response to targeted therapy. A current challenge to widespread utilization of case reports in clinical practice is the lack of systematic organization of clinical evidence across disease types, patient outcomes, therapies, and associated molecular features. To address this challenge, we sought to demonstrate the utility of Cancer Knowledgebase (CKB) (https://ckb.genomenon.com/) in interpreting oncology case report data for health care providers. We analyzed data from 5527 manually curated case reports in CKB to gain insights related to treatment options and patient response associated with specific molecular alterations. Each case report in CKB is represented as a unique efficacy evidence annotation and is associated with a specific molecular profile, therapy, indication, and response to therapy. Efficacy evidence from case reports spans over 500 genes, 2800 molecular profiles, and 300 tumor types, including several rare cancers and pediatric tumor types. CKB is a powerful resource for leveraging case reports to identify treatment options for patients with rare cancers and oncogenic variants, patients for whom multiple therapies exist, and patients experiencing resistance to first-line therapy.

Overcoming the barriers to treatment of rare cancer patients in the era of precision oncology: A call to action.

Retroperitoneal sarcoma (RPS) is a rare cancer, so few reports have previously characterized its national profiles. The capture rate of RPS in the Bone and Soft Tissue Tumor Registry was only 20%. The present study aimed to clarify the characteristics and clinical outcomes of RPS using the National Cancer Registry (NCR), which contains nationwide population-based data from Japan. We analyzed data from 20,079 patients with soft-tissue sarcomas (STS), entered into the NCR in 2016-2019 using the International Classification of Diseases-Oncology, Third Edition cancer topography and morphology codes. We extracted demographics (sex, age), tumor details (tumor location, histology, extent of disease), treatment, and prognosis for each patient. Of the 20,079 patients, 3311 patients were diagnosed with RPS. RPS accounts for 16.5% of all STS, with an adjusted incidence of 0.41/100,000/year. Of patients with RPS, 70.9% were aged 60 years or older and 52.7% were at the 'regional' stage at the time of diagnosis. Surgery was performed in 70.0% of cases, while chemotherapy and radiotherapy were performed in only 21.5% and 8.3% of cases, respectively. The 3-year overall survival (OAS) of the RPS patients was 57.3%. The multivariate analyses showed that of the 3,311 patients with RPS, worse OAS was associated with being male, older age, a histology of undifferentiated pleomorphic sarcoma/malignant fibrous histiocytoma, cancer discovery other than by cancer/health screening, being treated at low-volume hospitals, advanced disease, and not having surgery. The present study is the first to have clarified the epidemiology, clinical features, treatment, prognosis, and significant factors affecting prognosis of patients with RPS in Japan. Level Ⅲ, prognostic studies.

Development of succinate dehydrogenase subunit B-deficient tumor models for preclinical immunotherapy testing.

Pediatric pancreatic neuroblastoma is a rare cancer in children, with only limited cases available in the literature. We report a case of a 4-year-old girl diagnosed with high-risk pancreatic neuroblastoma. The girl was treated with induction chemotherapy followed by autologous stem cell transplant and maintenance with 13-cis-retinoic acid. Surgery and radiotherapy were not feasible due to the very small size of the mass postinduction, the location of the tumor, and the expected toxicities. The girl completed treatment successfully and is now 1 and a half years postautologous stem cell transplant without any evidence of disease.

Clinicopathological features and survival differences between G/GEJ-CSC and GAC: A Propensity score-matched, large-scale cross-population retrospective study.

Co-Designing a Quality of Life Survey for Mesothelioma: Qualitative and Cognitive Interview Findings.

Clinical Evaluation of Stereotactic Ablative Radiotherapy for Oligometastases From Rare Primary Cancers.

Quantifying evidence for phenotypic specificity (PP4) for syndromic phenotypes: Large-scale integration of rare germline FH variants from diagnostic laboratory testing for HLRCC and renal cancer.

How to foster new treatment development in ultra-rare tumours? Joint EMA-EORTC multi-stakeholder workshops on ultra-rare sarcomas as a model for rare cancers.

EPICYCLE: A confirmatory preclinical study of the anti-rhabdomyosarcoma efficacy of BET bromodomain and cyclin-dependent kinase 9 inhibitors.

As the predominant approach for pathological whole slide image (WSI) classification, multiple instance learning (MIL) methods struggle with limited labeled WSIs. Although MIL has achieved notable progress with pseudo-bag-oriented augmentation methods, their effectiveness is often constrained by noisy pseudo-labels and low-quality pseudo-bags. To overcome these problems, we revisit the use of pseudo-bags for WSI data augmentation and propose a new pseudo-bag generation paradigm, dubbed DPBAug. Its distinctive features can be summarized as: i) We develop an intra-slide pseudo-bag generation module, which separates the heterogeneous instances within each slide through phenotype partitioning. Moreover, to ensure accurate label inheritance when generating pseudo-bags, we propose an instance sampling algorithm with replacement. ii) An inter-slide pseudo-bag fusion module is designed to integrate heterogeneous information across multiple WSIs, producing high-quality training samples that better leverage the potential of neural networks. iii) A pseudo-bag memory update module prioritizes valuable synthetic pseudo-bags. This further enhances the network's classification performance. Extensive experiments demonstrate that DPBAug surpasses existing augmentation methods, enhancing the classification performance and reliability of multiple MIL baselines across various public datasets. DPBAug also improves the generalization and data efficiency of existing MIL methods, facilitating their adoption in clinical practice and rare cancer research The project is available at: https://github.com/JiuyangDong/DPBAug.

Basosquamous carcinoma (BSC) is a rare and aggressive cutaneous cancer with an increased risk of recurrence and metastasis. There are no specific clinical presentations of BSC, and the diagnosis is only made after biopsy. We report a case of histologically confirmed basosquamous carcinoma. We Report: A 70-year-old female patient with a personal history of treated nasopharyngeal tumor presented with a two-year history of a linear, ulcerated, bleeding-on-contact lesion on her face. A biopsy was performed, and histology revealed a tumor with mixed features of basal cell carcinoma combined with an area of squamous cell carcinoma, consistent with the morphological appearance of basosquamous carcinoma.

BackgroundCutaneous malignant melanoma is a common cancer in adults but extremely rare in young children, affecting fewer than one child per million each year in Europe. Because of its rarity, most treatments for children are adapted from adult therapies, despite possible biological differences. This study aimed to explore the molecular features of a rare and aggressive melanoma in a 16-month-old patient to understand disease progression and treatment resistance.MethodsWe studied the tumour and metastases of a patient with a melanoma carrying an NRAS mutation, who received chemotherapy and immune checkpoint inhibitor treatment. The patient died 10 months after diagnosis. We used DNA methylation analysis, single-nucleus RNA sequencing, and deep spatial transcriptomic profiling to examine genetic changes, gene activity, and their spatial distribution in both the primary tumour and lymph node metastases.ResultsHere, we show that the tumour displayed high genetic and transcriptomic diversity. We identified increases in MITF and BRAF gene copies as likely key drivers of the aggressive disease, which were not detected at diagnosis. We also found activation of biological pathways, including VEGFA and WNT signalling, and abnormal activity of several genes linked to immune therapy response, with marked variation between tumour regions.ConclusionsThis case demonstrates that paediatric melanoma can harbour complex and spatially variable molecular changes that contribute to rapid disease progression and treatment failure. Our findings support incorporating detailed spatial transcriptional profiling into clinical assessment to better guide therapy in rare paediatric cancers.