Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.

Cancer of unknown primary (CUP) is a rare type of metastatic cancer in which the origin of the tumor is unknown. Since the treatment strategy for patients with metastatic tumors depends on knowing the primary site, accurate identification of the origin site is important. Here, we developed an image-based deep-learning model that utilizes a vision transformer algorithm for predicting the origin of CUP. Using DNA methylation dataset of 8,233 primary tumors from The Cancer Genome Atlas (TCGA), we categorized 29 cancer types into 18 organ classes and extracted 2,312 differentially methylated CpG sites (DMCs) from non-squamous cancer group and 420 DMCs from squamous cell cancer group. Using these DMCs, we created organ-specific DNA methylation images and used them for model training and testing. Model performance was evaluated using 394 metastatic cancer samples from TCGA (TCGA-meta) and 995 samples (693 primary and 302 metastatic cancers) obtained from 20 independent external studies. We identified that the DNA methylation image reveals a distinct pattern based on the origin of cancer. Our model achieved an overall accuracy of 96.95 % in the TCGA-meta dataset. In the external validation datasets, our classifier achieved overall accuracies of 96.39 % and 94.37 % in primary and metastatic tumors, respectively. Especially, the overall accuracies for both primary and metastatic samples of non-squamous cell cancer were exceptionally high, with 96.79 % and 96.85 %, respectively.

LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features.

Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features. We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model. LORIS outperforms previous signatures in predicting ICB response and identifying responsive patients even with low tumor mutational burden or programmed cell death 1 ligand 1 expression. LORIS consistently predicts patient objective response and short-term and long-term survival across most cancer types. Moreover, LORIS showcases a near-monotonic relationship with ICB response probability and patient survival, enabling precise patient stratification. As an accurate, interpretable method using a few readily measurable features, LORIS may help improve clinical decision-making in precision medicine to maximize patient benefit. LORIS is available as an online tool at https://loris.ccr.cancer.gov/ .

Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression.

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

An immunogenetic basis for lung cancer risk.

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

Redox-Responsive Comparison of Diselenide and Disulfide Core-Cross-Linked Micelles for Drug Delivery Application.

In this study, diselenide (Se-Se) and disulfide (S-S) redox-responsive core-cross-linked (CCL) micelles were synthesized using poly(ethylene oxide)2k-b-poly(furfuryl methacrylate)1.5k (PEO2k-b-PFMA1.5k), and their redox sensitivity was compared. A single electron transfer-living radical polymerization technique was used to prepare PEO2k-b-PFMA1.5k from FMA monomers and PEO2k-Br initiators. An anti-cancer drug, doxorubicin (DOX), was incorporated into PFMA hydrophobic parts of the polymeric micelles, which were then cross-linked with maleimide cross-linkers, 1,6-bis(maleimide) hexane, dithiobis(maleimido) ethane and diselenobis(maleimido) ethane via Diels-Alder reaction. Under physiological conditions, the structural stability of both S-S and Se-Se CCL micelles was maintained; however, treatments with 10 mM GSH induced redox-responsive de-cross-linking of S-S and Se-Se bonds. In contrast, the S-S bond was intact in the presence of 100 mM H2O2, while the Se-Se bond underwent de-crosslinking upon the treatment. DLS studies revealed that the size and PDI of (PEO2k-b-PFMA1.5k-Se)2 micelles varied more significantly in response to changes in the redox environment than (PEO2k-b-PFMA1.5k-S)2 micelles. In vitro release studies showed that the developed micelles had a lower drug release rate at pH 7.4, whereas a higher release was observed at pH 5.0 (tumor environment). The micelles were non-toxic against HEK-293 normal cells, which revealed that they could be safe for use. Nevertheless, DOX-loaded S-S/Se-Se CCL micelles exhibited potent cytotoxicity against BT-20 cancer cells. Based on these results, the (PEO2k-b-PFMA1.5k-Se)2 micelles can be more sensitive drug carriers than (PEO2k-b-PFMA1.5k-S)2 micelles.

Redox-Responsive Core-Cross-Linked Micelles of Miktoarm Poly(ethylene oxide)-b-poly(furfuryl methacrylate) for Anticancer Drug Delivery.

The physiological instability of nanocarriers, premature drug leakage during blood circulation, and associated severe side effects cause compromised therapeutic efficacy, which have significantly hampered the progress of nanomedicines. The cross-linking of nanocarriers while keeping the effectiveness of their degradation at the targeted site to release the drug has emerged as a potent strategy to overcome these flaws. Herein, we have designed novel (poly(ethylene oxide))2-b-poly(furfuryl methacrylate) ((PEO2K)2-b-PFMAnk) miktoarm amphiphilic block copolymers by coupling alkyne-functionalized PEO (PEO2K-C≡H) and diazide-functionalized poly(furfuryl methacrylate) ((N3)2-PFMAnk) via click chemistry. (PEO2K)2-b-PFMAnk self-assembled to form nanosized micelles (mikUCL) with hydrodynamic radii in the range of 25∼33 nm. The hydrophobic core of mikUCL was cross-linked by a disulfide-containing cross-linker using the Diels-Alder reaction to avoid unwanted leakage and burst release of a payload. As expected, the resulting core-cross-linked (PEO2K)2-b-PFMAnk micelles (mikCCL) exhibited superior stability under a normal physiological environment and were de-cross-linked to rapidly release doxorubicin (DOX) upon exposure to a reduction environment. The micelles were compatible with HEK-293 normal cells, while DOX-loaded micelles (mikUCL/DOX and mikCCL/DOX) induced high antitumor activity in HeLa and HT-29 cells. mikCCL/DOX preferentially accumulated at the tumor site and was more efficacious than free DOX and mikUCL/DOX for tumor inhibition in HT-29 tumor-bearing nude mice.

Validation of a Machine Learning Model to Predict Immunotherapy Response in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous-cell carcinoma (HNSCC) is a disease with a generally poor prognosis; half of treated patients eventually develop recurrent and/or metastatic (R/M) disease. Patients with R/M HNSCC generally have incurable disease with a median survival of 10 to 15 months. Although immune-checkpoint blockade (ICB) has improved outcomes in patients with R/M HNSCC, identifying patients who are likely to benefit from ICB remains a challenge. Biomarkers in current clinical use include tumor mutational burden and immunohistochemistry for programmed death-ligand 1, both of which have only modest predictive power. Machine learning (ML) has the potential to aid in clinical decision-making as an approach to estimate a tumor's likelihood of response or a patient's likelihood of experiencing clinical benefit from therapies such as ICB. Previously, we described a random forest ML model that had value in predicting ICB response using 11 or 16 clinical, laboratory, and genomic features in a pan-cancer development cohort. However, its applicability to certain cancer types, such as HNSCC, has been unknown, due to a lack of cancer-type-specific validation. Here, we present the first validation of a random forest ML tool to predict the likelihood of ICB response in patients with R/M HNSCC. The tool had adequate predictive power for tumor response (area under the receiver operating characteristic curve = 0.65) and was able to stratify patients by overall (HR = 0.53 [95% CI 0.29-0.99], p = 0.045) and progression-free (HR = 0.49 [95% CI 0.27-0.87], p = 0.016) survival. The overall accuracy was 0.72. Our study validates an ML predictor in HNSCC, demonstrating promising performance in a novel cohort of patients. Further studies are needed to validate the generalizability of this algorithm in larger patient samples from additional multi-institutional contexts.

Metronomic dose-finding approach in oral chemotherapy by experimentally-driven integrative mathematical modeling.

In conventional chemotherapy, maximum tolerated dose approach is considered as a first-line medication for cancer treatment in clinics. In contrast to the conventional chemotherapy which has heavy tumor burdens arising from high dose treatment, metronomic chemotherapy (MCT) engages relatively low dose without drug-free breaks, and is recognized as a promising strategy for a long-term management of the disease. Although doxorubicin (DOX), an anthracycline anti-cancer drug, showed a potential of maintenance effect in vitro, further study on in vivo-relevant concentration to achieve tumor suppression with no toxicity is required to apply the MCT in clinicals. Therefore, the objective of this study was to identify an optimal MCT regimen of DOX by determining concentration-response relationships of tumor suppression (pharmacodynamic; PD) and cardiac toxicity (toxicodynamic; TD). Utilizing an oral DOX formulation complexed with deoxycholic acid (DOX/DOCA complex) which has enhanced bioavailability, physiologically-based pharmacokinetic (PBPK) model was linked to TD and PD models to generate drug profiles from the combined PK, TD, and PD parameters. The integrated model was validated for various scenarios of administration route, formulation, dose, and frequency. The established mathematical model facilitated calculations of adequate in vivo-relevant dosages and intervals, suggesting the optimum oral metronomic regimen of DOX. It is expected to serve as a useful guideline for the design and evaluation of oral DOX formulations in future preclinical/clinical studies.

Pre-treatment serum albumin and mutational burden as biomarkers of response to immune checkpoint blockade.

The effects of cytokine and protein stabilizing carriers, such as serum albumin, on tumor response to immune checkpoint blockade (ICB) is not well understood. By examining 1714 patients across 16 cancer types, we found that high pretreatment serum albumin level predicts favorable tumor radiographic response following ICB treatment in a dose-dependent fashion. Serum albumin is a candidate biomarker that can be combined with tumor mutational burden (TMB) for additional predictive capacity, and the tumor response rate to ICB was ~49% in the albumin-high/TMB-high group.

Improved prediction of immune checkpoint blockade efficacy across multiple cancer types.

Only a fraction of patients with cancer respond to immune checkpoint blockade (ICB) treatment, but current decision-making procedures have limited accuracy. In this study, we developed a machine learning model to predict ICB response by integrating genomic, molecular, demographic and clinical data from a comprehensively curated cohort (MSK-IMPACT) with 1,479 patients treated with ICB across 16 different cancer types. In a retrospective analysis, the model achieved high sensitivity and specificity in predicting clinical response to immunotherapy and predicted both overall survival and progression-free survival in the test data across different cancer types. Our model significantly outperformed predictions based on tumor mutational burden, which was recently approved by the U.S. Food and Drug Administration for this purpose1. Additionally, the model provides quantitative assessments of the model features that are most salient for the predictions. We anticipate that this approach will substantially improve clinical decision-making in immunotherapy and inform future interventions.

Near-Infrared Light-Responsive Shell-Crosslinked Micelles of Poly(d,l-lactide)-b-poly((furfuryl methacrylate)-co-(N-acryloylmorpholine)) Prepared by Diels-Alder Reaction for the Triggered Release of Doxorubicin.

In the present study, we developed near-infrared (NIR)-responsive shell-crosslinked (SCL) micelles using the Diels-Alder (DA) click reaction between an amphiphilic copolymer poly(d,l-lactide)20-b-poly((furfuryl methacrylate)10-co-(N-acryloylmorpholine)78) (PLA20-b-P(FMA10-co-NAM78)) and a diselenide-containing crosslinker, bis(maleimidoethyl) 3,3'-diselanediyldipropionoate (BMEDSeDP). The PLA20-b-P(FMA10-co-NAM78) copolymer was synthesized by RAFT polymerization of FMA and NAM using a PLA20-macro-chain transfer agent (PLA20-CTA). The DA reaction between BMEDSeDP and the furfuryl moieties in the copolymeric micelles in water resulted in the formation of SCL micelles. The SCL micelles were analyzed by 1H-NMR, FE-SEM, and DLS. An anticancer drug, doxorubicin (DOX), and an NIR sensitizer, indocyanine green (ICG), were effectively incorporated into the SCL micelles during the crosslinking reaction. The DOX/ICG-loaded SCL micelles showed pH- and NIR-responsive drug release, where burst release was observed under NIR laser irradiation. The in vitro cytotoxicity analysis demonstrated that the SCL was not cytotoxic against normal HFF-1 cells, while DOX/ICG-loaded SCL micelles exhibited significant antitumor activity toward HeLa cells. Thus, the SCL micelles of PLA20-b-P(FMA10-co-NAM78) can be used as a potential delivery vehicle for the controlled drug release in cancer therapy.

Microfluidic Airborne Metal Particle Sensor Using Oil Microcirculation for Real-Time and Continuous Monitoring of Metal Particle Emission.

Airborne metal particles (MPs; particle size > 10 µm) in workplaces result in a loss in production yield if not detected in time. The demand for compact and cost-efficient MP sensors to monitor airborne MP generation is increasing. However, contemporary instruments and laboratory-grade sensors exhibit certain limitations in real-time and on-site monitoring of airborne MPs. This paper presents a microfluidic MP detection chip to address these limitations. By combining the proposed system with microcirculation-based particle-to-liquid collection and a capacitive sensing method, the continuous detection of airborne MPs can be achieved. A few microfabrication processes were realized, resulting in a compact system, which can be easily replaced after contamination with a low-priced microfluidic chip. In our experiments, the frequency-dependent capacitive changes were characterized using MP (aluminum) samples (sizes ranging from 10 µm to 40 µm). Performance evaluation of the proposed system under test-bed conditions indicated that it is capable of real-time and continuous monitoring of airborne MPs (minimum size 10 µm) under an optimal frequency, with superior sensitivity and responsivity. Therefore, the proposed system can be used as an on-site MP sensor for unexpected airborne MP generation in precise manufacturing facilities where metal sources are used.

Phosphatidylserine-Gold Nanoparticles (PS-AuNP) Induce Prostate and Breast Cancer Cell Apoptosis.

Prostate and breast cancer are the current leading causes of new cancer cases in males and females, respectively. Phosphatidylserine (PS) is an essential lipid that mediates macrophage efferocytosis and is dysregulated in tumors. Therefore, developing therapies that selectively restore PS may be a potential therapeutic approach for carcinogenesis. Among the nanomedicine strategies for delivering PS, biocompatible gold nanoparticles (AuNPs) have an extensive track record in biomedical applications. In this study, we synthesized biomimetic phosphatidylserine-caped gold nanoparticles (PS-AuNPs) and tested their anticancer potential in breast and prostate cancer cells in vitro. We found that both cell lines exhibited changes in cell morphology indicative of apoptosis. After evaluating for histone-associated DNA fragments, a hallmark of apoptosis, we found significant increases in DNA fragmentation upon PS-AuNP treatment compared to the control treatment. These findings demonstrate the use of phosphatidylserine coupled with gold nanoparticles as a potential treatment for prostate and breast cancer. To the best of our knowledge, this is the first time that a phosphatidylserine-capped AuNP has been examined for its therapeutic potential in cancer therapy.

χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain.

Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are histopathological hallmarks in neurodegenerative diseases, has practical utilities in neuroscience and medicine. Here, we propose a biophysical model that describes the individual contribution of paramagnetic (e.g., iron) and diamagnetic (e.g., myelin) susceptibility sources to the frequency shift and transverse relaxation of MRI signals. Using this model, we develop a method, χ-separation, that generates the voxel-wise distributions of the two sources. The method is validated using computer simulation and phantom experiments, and applied to ex-vivo and in-vivo brains. The results delineate the well-known histological features of iron and myelin in the specimen, healthy volunteers, and multiple sclerosis patients. This new technology may serve as a practical tool for exploring the microstructural information of the brain.

Investigation of the Factors Responsible for the Poor Oral Bioavailability of Acacetin in Rats: Physicochemical and Biopharmaceutical Aspects.

Acacetin, an important ingredient of acacia honey and a component of several medicinal plants, exhibits therapeutic effects such as antioxidative, anticancer, anti-inflammatory, and anti-plasmodial activities. However, to date, studies reporting a systematic investigation of the in vivo fate of orally administered acacetin are limited. Moreover, the in vitro physicochemical and biopharmaceutical properties of acacetin in the gastrointestinal (GI) tract and their pharmacokinetic impacts remain unclear. Therefore, in this study, we aimed to systematically investigate the oral absorption and disposition of acacetin using relevant rat models. Acacetin exhibited poor solubility (≤119 ng/mL) and relatively low stability (27.5-62.0% remaining after 24 h) in pH 7 phosphate buffer and simulated GI fluids. A major portion (97.1%) of the initially injected acacetin dose remained unabsorbed in the jejunal segments, and the oral bioavailability of acacetin was very low at 2.34%. The systemic metabolism of acacetin occurred ubiquitously in various tissues (particularly in the liver, where it occurred most extensively), resulting in very high total plasma clearance of 199 ± 36 mL/min/kg. Collectively, the poor oral bioavailability of acacetin could be attributed mainly to its poor solubility and low GI luminal stability.

Crystal structures of human NSDHL and development of its novel inhibitor with the potential to suppress EGFR activity.

NAD(P)-dependent steroid dehydrogenase-like (NSDHL), an essential enzyme in human cholesterol synthesis and a regulator of epidermal growth factor receptor (EGFR) trafficking pathways, has attracted interest as a therapeutic target due to its crucial relevance to cholesterol-related diseases and carcinomas. However, the development of pharmacological agents for targeting NSDHL has been hindered by the absence of the atomic details of NSDHL. In this study, we reported two X-ray crystal structures of human NSDHL, which revealed a detailed description of the coenzyme-binding site and the unique conformational change upon the binding of a coenzyme. A structure-based virtual screening and biochemical evaluation were performed and identified a novel inhibitor for NSDHL harboring suppressive activity towards EGFR. In EGFR-driven human cancer cells, treatment with the potent NSDHL inhibitor enhanced the antitumor effect of an EGFR kinase inhibitor. Overall, these findings could serve as good platforms for the development of therapeutic agents against NSDHL-related diseases.

Therapeutic Efficacy of ABN401, a Highly Potent and Selective MET Inhibitor, Based on Diagnostic Biomarker Test in MET-Addicted Cancer.

The receptor tyrosine kinase c-MET regulates processes essential for tissue remodeling and mammalian development. The dysregulation of c-MET signaling plays a role in tumorigenesis. The aberrant activation of c-MET, such as that caused by gene amplification or mutations, is associated with many cancers. c-MET is therefore an attractive therapeutic target, and inhibitors are being tested in clinical trials. However, inappropriate patient selection criteria, such as low amplification or expression level cut-off values, have led to the failure of clinical trials. To include patients who respond to MET inhibitors, the selection criteria must include MET oncogenic addiction. Here, the efficacy of ABN401, a MET inhibitor, was investigated using histopathologic and genetic analyses in MET-addicted cancer cell lines and xenograft models. ABN401 was highly selective for 571 kinases, and it inhibited c-MET activity and its downstream signaling pathway. We performed pharmacokinetic profiling of ABN401 and defined the dose and treatment duration of ABN401 required to inhibit c-MET phosphorylation in xenograft models. The results show that the efficacy of ABN401 is associated with MET status and they highlight the importance of determining the cut-off values. The results suggest that clinical trials need to establish the characteristics of each sample and their correlations with the efficacy of MET inhibitors.

Genomic and Transcriptomic Characteristics According to Size of Papillary Thyroid Microcarcinoma.

It is controversial as to whether papillary thyroid microcarcinoma (PTMC) has some genomic and transcriptomic characteristics that differentiate between an early-stage lesion that would eventually evolve into the larger papillary thyroid cancer (PTC), and an occult indolent cancer in itself. To investigate this, we comprehensively elucidated the genomic and transcriptomic landscapes of PTMCs of different sizes, using a large-scaled database. This study included 3435 PTCs, 1985 of which were PTMCs. We performed targeted next-generation sequencing for 221 PTCs and integrated these data with the data including The Cancer Genome Atlas (TCGA) project. The frequency of v-raf murine sarcoma viral oncogene homolog B (BRAF)V600E mutation was higher in PTMCs >0.5 cm than that in very small PTMCs (≤0.5 cm) and decreased again in PTCs >2 cm. Among PTMCs, the prevalence of mutations in rat sarcoma (RAS) and telomerase reverse transcriptase (TERT) promoter was not significantly different according to their size, but lower than in large PTCs. There was no change in the tumor mutational burden, the number of driver mutations, and transcriptomic profiles with tumor size, among PTMCs and all PTCs. Although a few genes with differential expression and TERT promoter mutations were found in a few PTMCs, our findings showed that there were no useful genomic or transcriptomic characteristics for the prediction of the future progression of PTMC.

A novel small molecule STAT3 inhibitor SLSI-1216 suppresses proliferation and tumor growth of triple-negative breast cancer cells through apoptotic induction.

Triple-negative breast cancer (TNBC) is the most aggressive type of breast cancer, characterized by the lack of expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Owing to the absence of molecular targets, there are limited treatment options, and TNBC patients exhibit high mortality rates. Signal transducer and activator of transcription 3 (STAT3) is overexpressed and aberrantly activated in TNBC cells. Therefore, inhibition of STAT3-mediated signaling provides a potential strategy for the treatment of TNBC. In this study, A series of synthetic derivatives of SLSI-1 (a STAT3 inhibitor) were designed and evaluated for antitumor activity in TNBC cells. A novel derivative (SLSI-1216) exhibited the most potent anti-proliferative activity. SLSI-1216 effectively inhibited STAT3 activity and activation of STAT3, leading to the downregulation of AXL, a downstream target of STAT3 and epithelial-mesenchymal transition (EMT) progression. The inhibition of EMT by SLSI-1216 was associated with modulation of E-cadherin and N-cadherin. Furthermore, SLSI-1216 induced apoptosis by targeting STAT3 and effectively inhibited tumor growth in vivo. These findings suggest that SLSI-1216, as a potential inhibitor of STAT3, may be a promising therapeutic agent for TNBC.