Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling.

Introduction: Neoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow. Methods: In this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP). Results: We detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data. Discussion: This integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

epiTCR: a highly sensitive predictor for TCR-peptide binding.

MOTIVATION: Predicting the binding between T-cell receptor (TCR) and peptide presented by human leucocyte antigen molecule is a highly challenging task and a key bottleneck in the development of immunotherapy. Existing prediction tools, despite exhibiting good performance on the datasets they were built with, suffer from low true positive rates when used to predict epitopes capable of eliciting T-cell responses in patients. Therefore, an improved tool for TCR-peptide prediction built upon a large dataset combining existing publicly available data is still needed. RESULTS: We collected data from five public databases (IEDB, TBAdb, VDJdb, McPAS-TCR, and 10X) to form a dataset of >3 million TCR-peptide pairs, 3.27% of which were binding interactions. We proposed epiTCR, a Random Forest-based method dedicated to predicting the TCR-peptide interactions. epiTCR used simple input of TCR CDR3ß sequences and antigen sequences, which are encoded by flattened BLOSUM62. epiTCR performed with area under the curve (0.98) and higher sensitivity (0.94) than other existing tools (NetTCR, Imrex, ATM-TCR, and pMTnet), while maintaining comparable prediction specificity (0.9). We identified seven epitopes that contributed to 98.67% of false positives predicted by epiTCR and exerted similar effects on other tools. We also demonstrated a considerable influence of peptide sequences on prediction, highlighting the need for more diverse peptides in a more balanced dataset. In conclusion, epiTCR is among the most well-performing tools, thanks to the use of combined data from public sources and its use will contribute to the quest in identifying neoantigens for precision cancer immunotherapy. AVAILABILITY AND IMPLEMENTATION: epiTCR is available on GitHub (https://github.com/ddiem-ri-4D/epiTCR).

Fragment length profiles of cancer mutations enhance detection of circulating tumor DNA in patients with early-stage hepatocellular carcinoma.

BACKGROUND: Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. METHODS: Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. RESULTS: Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. CONCLUSIONS: Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Circulating DNA methylation profile improves the accuracy of serum biomarkers for the detection of nonmetastatic hepatocellular carcinoma.

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, µTASWako®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

The early detection of liver cancer in high-risk populations can help people with the disease have a higher chance of survival and better quality of life. However, this is still a healthcare challenge. Current commercial blood tests measuring protein signatures in the blood have low accuracy due to increased levels of these proteins being detected in both liver cancer patients and patients with chronic liver diseases. In this study, we identified a set of signatures in DNA released by cancer cells into the bloodstream and used them as biomarkers to distinguish liver cancer patients from high-risk patients. We also demonstrated that adding those signatures to a commercial blood test currently used in clinics could improve the accuracy in detecting liver cancer patients.

Efficacy of nimotuzumab (hR3) conjugated with 131I or 90Y in laryngeal carcinoma xenograft mouse model.

PURPOSE: The humanized monoclonal antibody hR3, both alone and in combination with other chemotherapeutic agents and radiotherapy, can be used to treat head and neck cancers. Substantial progress has been made in the development of targeted radioimmunotherapy using iodine-131 (131I) and yttrium-90 (90Y) radioisotopes in recent years. In the present study, we examined the efficacy of hR3 conjugated with 131I or 90Y to inhibit tumor growth in a laryngeal carcinoma xenograft tumor model. METHODS: hR3 was labeled with 131I or 90Y to generate the conjugates 131I-hR3 or 90Y-hR3. The conjugates were incubated with HEp-2 laryngeal carcinoma cells to evaluate binding capacity. The efficacy of the labeled hR3 conjugates to treat laryngeal cancer was also evaluated in nude mice inoculated with HEp-2 tumors. RESULTS: The purified radioimmunoconjugates with specific activities of 187-191 MBq/mg had radiochemical purity >98% and >80% immunoreactivity with HEp-2 cells. Mice with HEp-2 xenografts treated with 131I-hR3 or 90Y-hR3 showed reduced tumor volume and improved survival rates compared to the untreated control group and the group treated with unlabeled hR3. At equivalent doses, radioimmunotherapeutic hR3 labeled with 90Y had increased tumor inhibition activity compared to hR3 labeled with 131I. CONCLUSIONS: 131I-hR3 and 90Y-hR3 are promising targeted radiopharmaceuticals for treatment of head and neck cancers, especially laryngeal cancers.

Diverse Roles of TRPV4 in Macrophages: A Need for Unbiased Profiling.

Transient receptor potential vanilloid 4 (TRPV4) is a non-selective mechanosensitive ion channel expressed by various macrophage populations. Recent reports have characterized the role of TRPV4 in shaping the activity and phenotype of macrophages to influence the innate immune response to pathogen exposure and inflammation. TRPV4 has been studied extensively in the context of inflammation and inflammatory pain. Although TRPV4 activity has been generally described as pro-inflammatory, emerging evidence suggests a more complex role where this channel may also contribute to anti-inflammatory activities. However, detailed understanding of how TRPV4 may influence the initiation, maintenance, and resolution of inflammatory disease remains limited. This review highlights recent insights into the cellular processes through which TRPV4 contributes to pathological conditions and immune processes, with a focus on macrophage biology. The potential use of high-throughput and omics methods as an unbiased approach for studying the functional outcomes of TRPV4 activation is also discussed.

Induction of Paracrine Signaling in Metastatic Melanoma Cells by PPARγ Agonist Rosiglitazone Activates Stromal Cells and Enhances Tumor Growth.

In addition to improving insulin sensitivity in type 2 diabetes, the thiazolidinedione family of compounds and the pharmacologic activation of their best-characterized target PPARγ have been proposed as a therapeutic option for cancer treatment. In this study, we reveal a new mode of action for the thiazolidinedione rosiglitazone that can contribute to tumorigenesis. Rosiglitazone activated a tumorigenic paracrine communication program in a subset of human melanoma cells that involves the secretion of cytokines, chemokines, and angiogenic factors. This complex blend of paracrine signals activated nonmalignant fibroblasts, endothelial cells, and macrophages in a tumor-friendly way. In agreement with these data, rosiglitazone promoted human melanoma development in xenografts, and tumors exposed to rosiglitazone exhibited enhanced angiogenesis and inflammation. Together, these findings establish an important tumorigenic action of rosiglitazone in a subset of melanoma cells. Although studies conducted on cohorts of diabetic patients report overall benefits of thiazolidinediones in cancer prevention, our data suggest that exposure of established tumors to rosiglitazone may be deleterious.Significance: These findings uncover a novel mechanism by which the thiazolidinedione compound rosiglitazone contributes to tumorigenesis, thus highlighting a potential risk associated with its use in patients with established tumors. Cancer Res; 78(22); 6447-61. ©2018 AACR.

Music therapy to reduce pain and anxiety in children with cancer undergoing lumbar puncture: a randomized clinical trial.

A nonpharmacological method can be an alternative or complement to analgesics.The aim of this study was to evaluate if music medicine influences pain and anxiety in children undergoing lumbar punctures. A randomized clinical trial was used in 40 children (aged 7-12 years) with leukemia, followed by interviews in 20 of these participants. The participants were randomly assigned to a music group (n = 20) or control group (n = 20). The primary outcome was pain scores and the secondary was heart rate, blood pressure, respiratory rate, and oxygen saturation measured before, during, and after the procedure. Anxiety scores were measured before and after the procedure. Interviews with open-ended questions were conducted in conjunction with the completed procedures. The results showed lower pain scores and heart and respiratory rates in the music group during and after the lumbar puncture. The anxiety scores were lower in the music group both before and after the procedure. The findings from the interviews confirmed the quantity results through descriptions of a positive experience by the children, including less pain and fear.