TOTEM: a multi-cancer detection and localization approach using circulating tumor DNA methylation markers.

BACKGROUND: Detection of cancer and identification of tumor origin at an early stage improve the survival and prognosis of patients. Herein, we proposed a plasma cfDNA-based approach called TOTEM to detect and trace the cancer signal origin (CSO) through methylation markers. METHODS: We performed enzymatic conversion-based targeted methylation sequencing on plasma cfDNA samples collected from a clinical cohort of 500 healthy controls and 733 cancer patients with seven types of cancer (breast, colorectum, esophagus, stomach, liver, lung, and pancreas) and randomly divided these samples into a training cohort and a testing cohort. An independent validation cohort of 143 healthy controls, 79 liver cancer patients and 100 stomach cancer patients were recruited to validate the generalizability of our approach. RESULTS: A total of 57 multi-cancer diagnostic markers and 873 CSO markers were selected for model development. The binary diagnostic model achieved an area under the curve (AUC) of 0.907, 0.908 and 0.868 in the training, testing and independent validation cohorts, respectively. With a training specificity of 98%, the specificities in the testing and independent validation cohorts were 100% and 98.6%, respectively. Overall sensitivity across all cancer stages was 65.5%, 67.3% and 55.9% in the training, testing and independent validation cohorts, respectively. Early-stage (I and II) sensitivity was 50.3% and 45.7% in the training and testing cohorts, respectively. For cancer patients correctly identified by the binary classifier, the top 1 and top 2 CSO accuracies were 77.7% and 86.5% in the testing cohort (n = 148) and 76.0% and 84.0% in the independent validation cohort (n = 100). Notably, performance was maintained with only 21 diagnostic and 214 CSO markers, achieving a training AUC of 0.865, a testing AUC of 0.866, and an integrated top 2 accuracy of 83.1% in the testing cohort. CONCLUSIONS: TOTEM demonstrates promising potential for accurate multi-cancer detection and localization by profiling plasma methylation markers. The real-world clinical performance of our approach needs to be investigated in a much larger prospective cohort.

A novel approach to cancer screening using the nematode Caenorhabditis elegans-based detection assays.

BACKGROUND: Early diagnosis of cancer is essential for its effective treatment. Currently, established screening tests are cancer-specific and require screening for each type of cancer separately. The primary objective of cancer research is to develop methods that can detect multiple types of tumors from a single body fluid sample. Multicancer early detection tests aim to detect fragments of circulating tumor DNA, cell-free DNA, circulating microRNAs, or proteins released by cancer cells in the patient's body fluids. However, these tests are not suitable for routine cancer prevention due to their high cost. Therefore, in recent years, cancer screening tests have been developed to detect volatile organic compounds in urine using living organisms, such as nematodes, Caenorhabditis elegans. Measuring only 1 mm in length, C. elegans has the potential to offer a new, efficient, cost-effective, quick, and painless method to detect the presence of tumor. PURPOSE: The purpose of this review is to present an overview of the literature on the development and validation of C. elegans-based cancer detection methods. The potential benefits of these assays are significant, as they could become a valuable tool for the early identification and diagnosis of cancer, even though this research is still in its initial stages of development.

[Epidemiological signatures and surveillance bias in cancer]. / Signatures épidémiologiques et biais de surveillance du cancer.

Surveillance bias occurs when variations in cancer incidence are the result of changes in screening or diagnostic practices rather than increases in the true occurrence of cancer. This bias is linked to the issue of overdiagnosis and can be apprehended by looking at epidemiological signatures of cancer. We explain the concept of epidemiological signatures using the examples of melanoma and of lung and prostate cancer. Accounting for surveillance bias is particularly important for assessing the true burden of cancer and for accurately communicating cancer information to the population and decision-makers.

Le biais de surveillance se produit lorsque les variations d'incidence d'un cancer sont le résultat d'un changement dans les pratiques de dépistage ou de diagnostic plutôt que d'une augmentation de la fréquence réelle de ce cancer. Ce biais est lié au concept du surdiagnostic et peut être appréhendé en examinant les signatures épidémiologiques des cancers. Nous expliquons le concept de signature épidémiologique à l'aide des exemples du mélanome et des cancers du poumon et de la prostate. La prise en compte des biais de surveillance est particulièrement importante pour évaluer le fardeau réel du cancer et communiquer avec précision l'information sur le cancer à la population et aux décideurs.

When Will Real-World Data Fulfill Its Promise to Provide Timely Insights in Oncology?

Randomized trials provide high-quality, internally consistent data on selected clinical questions, but lack generalizability for the aging population who are most often diagnosed with cancer and have comorbid conditions that may affect the interpretation of treatment benefit. The need for high-quality, relevant, and timely data is greater than ever. Promising solutions lie in the collection and analysis of real-world data (RWD), which can potentially provide timely insights about the patient's course during and after initial treatment and the outcomes of important subgroups such as the elderly, rural populations, children, and patients with greater social health needs. However, to inform practice and policy, real-world evidence must be created from trustworthy and comprehensive sources of RWD; these may include pragmatic clinical trials, registries, prospective observational studies, electronic health records (EHRs), administrative claims, and digital technologies. There are unique challenges in oncology since key parameters (eg, cancer stage, biomarker status, genomic assays, imaging response, side effects, quality of life) are not recorded, siloed in inaccessible documents, or available only as free text or unstructured reports in the EHR. Advances in analytics, such as artificial intelligence, may greatly enhance the ability to obtain more granular information from EHRs and support integrated diagnostics; however, they will need to be validated purpose by purpose. We recommend a commitment to standardizing data across sources and building infrastructures that can produce fit-for-purpose RWD that will provide timely understanding of the effectiveness of individual interventions.

From biogenesis to aptasensors: advancements in analysis for tumor-derived extracellular vesicles research.

Extracellular vesicles (EVs) are enclosed by a nanoscale phospholipid bilayer membrane and typically range in size from 30 to 200 nm. They contain a high concentration of specific proteins, nucleic acids, and lipids, reflecting but not identical to the composition of the parent cell. The inherent characteristics and variety of EVs give them extensive and unique advantages in the field of cancer identification and treatment. Recently, EVs have been recognized as potential tumor markers for the detection of cancer. Aptamers, which are molecules of single-stranded DNA or RNA, demonstrate remarkable specificity and affinity for their targets by adopting distinct tertiary structures. Aptamers offer various advantages over their protein counterparts, such as reduced immunogenicity, the ability for convenient large-scale synthesis, and straightforward chemical modification. In this review, we summarized EVs biogenesis, sample collection, isolation, storage and characterization, and finally provided a comprehensive survey of analysis techniques for EVs detection that are based on aptamers.

Application of Photoactive Compounds in Cancer Theranostics: Review on Recent Trends from Photoactive Chemistry to Artificial Intelligence.

According to the World Health Organization (WHO) and the International Agency for Research on Cancer (IARC), the number of cancer cases and deaths worldwide is predicted to nearly double by 2030, reaching 21.7 million cases and 13 million fatalities. The increase in cancer mortality is due to limitations in the diagnosis and treatment options that are currently available. The close relationship between diagnostics and medicine has made it possible for cancer patients to receive precise diagnoses and individualized care. This article discusses newly developed compounds with potential for photodynamic therapy and diagnostic applications, as well as those already in use. In addition, it discusses the use of artificial intelligence in the analysis of diagnostic images obtained using, among other things, theranostic agents.

Innovative use of Australian cancer registry data for early detection of the effects of epidemics and other mass disruptions on cancer incidence.

BACKGROUND: Predictive modelling using pre-epidemic data have long been used to guide public health responses to communicable disease outbreaks and other health disruptions. In this study, cancer registry and related health data available 2-3 months from diagnosis were used to predict changes in cancer detection that otherwise would not have been identified until full registry processing was completed about 18-24 months later. A key question was whether these earlier data could be used to predict cancer incidence ahead of full processing by the cancer registry as a guide to more timely health responses. The setting was the Australian State of New South Wales, covering 31 % of the Australian population. The study year was 2020, the year of emergence of the COVID-19 pandemic. METHODS: Cancer detection in 2020 was modelled using data available 2-3 months after diagnosis. This was compared with data from full registry processing available from 2022. Data from pre-pandemic 2018 were used for exploratory model building. Models were tested using pre-pandemic 2019 data. Candidate predictor variables included pathology, surgery and radiation therapy reports, numbers of breast screens, colonoscopies, PSA tests, and melanoma excisions recorded by the universal Medical Benefits Schedule (MBS). Data were analysed for all cancers collectively and 5 leading types. RESULTS: Compared with full registry processing, modelled data for 2020 had a >95 % accuracy overall, indicating key points of inflexion of cancer detection over the COVID-disrupted 2020 period. These findings highlight the potential of predictive modelling of cancer-related data soon after diagnosis to reveal changes in cancer detection during epidemics and other health disruptions. CONCLUSIONS: Data available 2-3 months from diagnosis in the pandemic year indicated changes in cancer detection that were ultimately confirmed by fully-processed cancer registry data about 24 months later. This indicates the potential utility of using these early data in an early-warning system.

hTERT Epigenetics Provides New Perspectives for Diagnosis and Evidence-Based Guidance of Chemotherapy in Cancer.

Strong epigenetic pan-cancer biomarkers are required to meet several current, urgent clinical needs and to further improve the present chemotherapeutic standard. We have concentrated on the investigation of epigenetic alteration of the hTERT gene, which is frequently epigenetically dysregulated in a number of cancers in specific developmental stages. Distinct DNA methylation profiles were identified in our data on early urothelial cancer. An efficient EpihTERT assay could be developed utilizing suitable combinations with sequence-dependent thermodynamic parameters to distinguish between differentially methylated states. We infer from this data set, the epigenetic context, and the related literature that a CpG-rich, 2800 bp region, a prominent CpG island, surrounding the transcription start of the hTERT gene is the crucial epigenetic zone for the development of a potent biomarker. In order to accurately describe this region, we have named it "Acheron" (Ἀχέρων). In Greek mythology, this is the river of woe and misery and the path to the underworld. Exploitation of the DNA methylation profiles focused on this region, e.g., idiolocal normalized Methylation Specific PCR (IDLN-MSP), opens up a wide range of new possibilities for diagnosis, determination of prognosis, follow-up, and detection of residual disease. It may also have broad implications for the choice of chemotherapy.

Housing Status and Acute Care Use After Cancer Diagnosis.

This cohort study examines housing status and acute care use after a cancer diagnosis among individuals treated at a public hospital in San Francisco, California.

Graphene-based hybrid composites for cancer diagnostic and therapy.

The application of graphene-based nanocomposites for therapeutic and diagnostic reasons has advanced considerably in recent years due to advancements in the synthesis and design of graphene-based nanocomposites, giving rise to a new field of nano-cancer diagnosis and treatment. Nano-graphene is being utilized more often in the field of cancer therapy, where it is employed in conjunction with diagnostics and treatment to address the complex clinical obstacles and problems associated with this life-threatening illness. When compared to other nanomaterials, graphene derivatives stand out due to their remarkable structural, mechanical, electrical, optical, and thermal capabilities. The high specific surface area of these materials makes them useful as carriers in controlled release systems that respond to external stimuli; these compounds include drugs and biomolecules like nucleic acid sequences (DNA and RNA). Furthermore, the presence of distinctive sheet-like nanostructures and the capacity for photothermal conversion have rendered graphene-based nanocomposites highly favorable for optical therapeutic applications, including photothermal treatment (PTT), photodynamic therapy (PDT), and theranostics. This review highlights the current state and benefits of using graphene-based nanocomposites in cancer diagnosis and therapy and discusses the obstacles and prospects of their future development. Then we focus on graphene-based nanocomposites applications in cancer treatment, including smart drug delivery systems, PTT, and PDT. Lastly, the biocompatibility of graphene-based nanocomposites is also discussed to provide a unique overview of the topic.

The role of exosomal molecular cargo in exosome biogenesis and disease diagnosis.

Exosomes represent a type of extracellular vesicles derived from the endosomal pathway that transport diverse molecular cargoes such as proteins, lipids, and nucleic acids. These cargoes have emerged as crucial elements impacting disease diagnosis, treatment, and prognosis, and are integral to the process of exosome formation. This review delves into the essential molecular cargoes implicated in the phases of exosome production and release. Emphasis is placed on their significance as cancer biomarkers and potential therapeutic targets, accompanied by an exploration of the obstacles and feasible applications linked to these developments.

Tissue of origin detection for cancer tumor using low-depth cfDNA samples through combination of tumor-specific methylation atlas and genome-wide methylation density in graph convolutional neural networks.

BACKGROUND: Cell free DNA (cfDNA)-based assays hold great potential in detecting early cancer signals yet determining the tissue-of-origin (TOO) for cancer signals remains a challenging task. Here, we investigated the contribution of a methylation atlas to TOO detection in low depth cfDNA samples. METHODS: We constructed a tumor-specific methylation atlas (TSMA) using whole-genome bisulfite sequencing (WGBS) data from five types of tumor tissues (breast, colorectal, gastric, liver and lung cancer) and paired white blood cells (WBC). TSMA was used with a non-negative least square matrix factorization (NNLS) deconvolution algorithm to identify the abundance of tumor tissue types in a WGBS sample. We showed that TSMA worked well with tumor tissue but struggled with cfDNA samples due to the overwhelming amount of WBC-derived DNA. To construct a model for TOO, we adopted the multi-modal strategy and used as inputs the combination of deconvolution scores from TSMA with other features of cfDNA. RESULTS: Our final model comprised of a graph convolutional neural network using deconvolution scores and genome-wide methylation density features, which achieved an accuracy of 69% in a held-out validation dataset of 239 low-depth cfDNA samples. CONCLUSIONS: In conclusion, we have demonstrated that our TSMA in combination with other cfDNA features can improve TOO detection in low-depth cfDNA samples.

Benefits for children with suspected cancer from routine whole-genome sequencing.

Clinical whole-genome sequencing (WGS) has been shown to deliver potential benefits to children with cancer and to alter treatment in high-risk patient groups. It remains unknown whether offering WGS to every child with suspected cancer can change patient management. We collected WGS variant calls and clinical and diagnostic information from 281 children (282 tumors) across two English units (n = 152 from a hematology center, n = 130 from a solid tumor center) where WGS had become a routine test. Our key finding was that variants uniquely attributable to WGS changed the management in ~7% (20 out of 282) of cases while providing additional disease-relevant findings, beyond standard-of-care molecular tests, in 108 instances for 83 (29%) cases. Furthermore, WGS faithfully reproduced every standard-of-care molecular test (n = 738) and revealed several previously unknown genomic features of childhood tumors. We show that WGS can be delivered as part of routine clinical care to children with suspected cancer and can change clinical management by delivering unexpected genomic insights. Our experience portrays WGS as a clinically impactful assay for routine practice, providing opportunities for assay consolidation and for delivery of molecularly informed patient care.

Disparity in cognitive factors related to cancer screening uptake based on the theory of planned behavior.

INTRODUCTION: Early detection of cancer is a highly effective way to decrease cancer-related deaths. The purpose of this study was to determine the disparity in cognitive factors related to cancer screening uptake based on the theory of planned behavior (TPB). METHODS: In this cross-sectional study, conducted in Kermanshah County, the west of Iran, during 2019, a total of 1760 people aged 30 to 75 years old, were randomly selected to participate voluntarily in the study. Participants filled out a questionnaire including the socio demographic variables, socioeconomic status (SES), TPB variables, and cancer screening uptake behaviors. RESULTS: The mean age of respondents was 45.28. 44.96% of the participants had undergone cancer screening at least once. Socioeconomic status (SES) and gender had the most significant impact on the disparity in cancer screening uptake, with contributions of 74.64% and 22.25% respectively. Women were 8.63 times more likely to be screened than men. Participants with a family history of cancer had a 2.84 times higher chance of being screened. Single individuals were significantly less likely to be screened compared to married individuals. The concentration index for attitude, subjective norms (SN), perceived behavior control (PBC), behavior intention, and cancer screening uptake was 0.0735, 0.113, 0.333, 0.067, and 0.132 respectively. Intention (Beta = 0.225 and P: < 0.001) is a significant predictor of cancer screening behaviors. CONCLUSION: The findings of this study are highly valuable for health policymakers in Iran. They emphasize the significance of creating, executing, and assessing campaigns that promote intention, PBC and SN, particularly among disadvantaged individuals. By doing so, we can effectively decrease the disparity in cancer screening rates. It is crucial to prioritize men, single individuals, and disadvantaged groups in cancer screening promotion programs. This knowledge can be utilized to develop an intervention that is guided by theory and supported by evidence, with the aim of increasing cancer screening rates and minimizing disparities.

DR-70 (fibrinogen-fibrin degradation products) as a prognostic biomarker in dogs with neoplasms.

Fibrinogen-fibrin degradation products (DR-70) are derived from tumor cells or metastases. Our previous study reported the diagnostic values in dogs with tumors, but no research has yet to be conducted to establish DR-70 as a prognostic marker. Herein, we investigated changes in DR-70 concentrations and disease courses in dogs with tumors. Overall survival time (OST) analysis was performed in 195 dogs with tumors, stratified with a recommended cut-off (1.514 µg/mL). Continual DR-70 measurements were performed during the medical interventions of 27 dogs with neoplasms. Clinical conditions and medical records were retrospectively reviewed. According to a cut-off value, dogs with plasma DR-70 concentrations above 1.514 µg/mL had shorter survival rates than those with concentrations below this threshold. In cases with complete or partial remission in response to treatment, the DR-70 concentration was decreased compared with that at the first visit, whereas it was increased in patients with disease progression. Our study suggested that changes in DR-70 concentration can be used as a prognostic biomarker for canine neoplasms. Furthermore, increased plasma DR-70 levels might be associated with shorter survival, and DR-70 concentrations may reflect responses to medical intervention.

Tumor de células gigantes esternal: esternectomía total y reconstrucción con barras de titanio más malla de polipropileno / Sternal Giant Cell Tumor: Total Sternectomy and Reconstruction with Titanium Rods Plus Polypropylene Mesh

El tumor de células gigantes (TCG) constituye un tumor óseo benigno relativamente frecuente. Se caracteriza por ser localmente agresivo y el lugar de presentación más frecuente es a nivel del esqueleto axial (fémur distal o tibia proximal). Hasta la actualidad, existen escasos informes de presentaciones atípicas, como a nivel del esternón. En este informe, se presenta el caso de una paciente mujer de 24 años que presenta tumoración indurada a nivel de la región esternal de crecimiento progresivo asociado a dolor. Los hallazgos radiológicos revelan tumoración osteolítica que tiene como origen el cuerpo del esternón y lo compromete casi en su totalidad. Este se proyecta hacia las partes blandas y llega al plano superficial. Debido a la extensión de la enfermedad y al compromiso extenso en el cuerpo del esternón, se realiza la resección del cuerpo y manubrio esternal. El defecto es reconstruido con malla de polipropileno, barras de titanio, parche de epiplón y autoinjerto de piel; se obtiene una adecuada estabilidad de la caja torácica y resultados estéticos favorables. El caso tiene un adecuado manejo oncológico puesto que la resección es completa con márgenes microscópicos libres (resección R0).

Giant cell tumor (GCT) constitutes a relatively common benign bone tumor, characteri-zed by its local aggressiveness. The most frequent site of occurrence is in the axial ske-leton (distal femur or proximal tibia). To date, there have been few reports of atypical presentations, such as at the level of the sternum. In this report, we present the case of a 24-year-old female patient who presented with an indurated mass in the sternal region, progressively growing and associated with pain. Radiological findings revealed an osteolytic mass originating from the body of the sternum, involving almost its entire extent and projecting into the soft tissues, reaching the superficial plane. Due to the extent of the disease and the extensive involvement of the sternal body, resection of the body and manubrium of the sternum was performed. The surgical defect was reconstructed with polypropylene mesh, titanium bars, an omental patch and a skin graft, achieving adequate stability of the thoracic cage and favorable cosmetic results.

Parallel DNA/RNA NGS Using an Identical Target Enrichment Panel in the Analysis of Hereditary Cancer Predisposition.

Germline DNA testing using the next-gene-ration sequencing (NGS) technology has become the analytical standard for the diagnostics of hereditary diseases, including cancer. Its increasing use places high demands on correct sample identification, independent confirmation of prioritized variants, and their functional and clinical interpretation. To streamline these processes, we introduced parallel DNA and RNA capture-based NGS using identical capture panel CZECANCA, which is routinely used for DNA analysis of hereditary cancer predisposition. Here, we present the analytical workflow for RNA sample processing and its analytical and diagnostic performance. Parallel DNA/RNA analysis allowed credible sample identification by calculating the kinship coefficient. The RNA capture-based approach enriched transcriptional targets for the majority of clinically relevant cancer predisposition genes to a degree that allowed analysis of the effect of identified DNA variants on mRNA processing. By comparing the panel and whole-exome RNA enrichment, we demonstrated that the tissue-specific gene expression pattern is independent of the capture panel. Moreover, technical replicates confirmed high reproducibility of the tested RNA analysis. We concluded that parallel DNA/RNA NGS using the identical gene panel is a robust and cost-effective diagnostic strategy. In our setting, it allows routine analysis of 48 DNA/RNA pairs using NextSeq 500/550 Mid Output Kit v2.5 (150 cycles) in a single run with sufficient coverage to analyse 226 cancer predisposition and candidate ge-nes. This approach can replace laborious Sanger confirmatory sequencing, increase testing turnaround, reduce analysis costs, and improve interpretation of the impact of variants by analysing their effect on mRNA processing.

Implementation of Universal Pan-Cancer Germline Genetic Testing in an Arab Population: The Jordanian Exploratory Cancer Genetics Study.

PURPOSE: Germline genetic testing (GGT) significantly affects cancer care. While universal testing has been studied in Western societies, less is known about adoption elsewhere. MATERIALS AND METHODS: In this study, 3,319 unselected, pan-cancer Jordanian patients diagnosed between April 2021 and September 2022 received GGT. Pathogenic germline variant (PGV) frequency among patients who were in-criteria (IC) or out-of-criteria (OOC; 2020 National Comprehensive Cancer Network criteria) and changes in clinical management in response to GGT results were evaluated. Statistical analysis was performed using two-tailed Fisher's exact test with significance level P < .05. RESULTS: The cohort was predominantly female (69.9%), with a mean age of 53.7 years at testing, and 53.1% were IC. While patients who were IC were more likely than patients who were OOC to have a PGV (15.8% v 9.6%; P < .0001), 149 (34.8%) patients with PGVs were OOC. Clinical management recommendations in response to GGT, including changes to treatment and/or follow-up, were made for 57.3% (161 of 281) of patients with high- or moderate-risk PGVs, including 26.1% (42 of 161) of patients who were OOC. CONCLUSION: Universal GGT of patients with newly diagnosed cancer was successfully implemented in Jordan and led to identification of actionable PGVs that would have been missed with guidelines-based testing.