Published papers

747Background: Tumor-informed circulating tumor DNA (ctDNA) assays for minimal residual disease (MRD) have demonstrated promise across multiple cancers. However, in pancreatic ductal adenocarcinoma (PDAC), clinical utility remains uncertain. We therefore conducted the multicenter prospective ARTEMIS-PC study to evaluate the utility of a personalized, tumor-informed MRD assay in patients with resectable PDAC. Methods: Of 50 patients who underwent panel creation, 40 (80%) were successful. Among these, 39 patients with treatment-naïve, preoperative tumor tissue and histopathologic confirmation of PDAC, as well as assessable longitudinal ctDNA, were included in the analysis. ctDNA was assessed using a patient-specific, tumor-informed assay (Invitae Personalized Cancer Monitoring). Plasma was collected longitudinally at specific timepoints: enrollment, after completion of neoadjuvant chemotherapy (NAC) when administered (36/39), 1 month postoperatively, every 3 months during year 1, and every 6 months thereafter through 24 months. Endpoints included panel-creation success rate, longitudinal ctDNA dynamics, and associations of ctDNA status with landmark recurrence-free survival (RFS) and overall survival (OS). Results: The majority of resectable patients in study were stage I (IA-12, 31%; IB-24, 62%) at diagnosis, with a small subset being stage II (IIA-1, 2%; IIB-2, 5%). The median follow-up period was 17.7 months (range: 2.1-30.7 months). At baseline, 67% (26/39) patients were ctDNA positive. Among ctDNA-positive who received NAC (22/26), 45% (10/22) converted to negative, whereas 55% (12/22) remained positive. 50% (8/16) of ctDNA-positive patients were inoperable. Among 29 patients who underwent surgery, 21 (72.4%) remained ctDNA-negative, 6 (20.7%) converted to negative, and 2 (6.9%) remained positive at 1 month postoperatively. Recurrence occurred in 16 patients (55.2%), with a median lead time of 0 months (range: 0-6) in 12 evaluable patients, 4/12 had a 2-6 month lead time compared to imaging; 3/16 patients (18.8%) remained ctDNA-negative at recurrence, ctDNA positivity after NAC (if given)/ before surgery was associated with significantly worse RFS (HR = 4.69; P = .005) and OS (HR = 15.75; P = .031). Median RFS was 16.5 months for ctDNA-negative vs 4.6 months for ctDNA-positive. ctDNA negativity after NAC (if given)/before surgery remained the strongest independent predictor of RFS on multivariable analysis (HR = 3.95; P = .025). Conclusions: Tumor-informed ctDNA monitoring is feasible in patients with resectable PDAC. ctDNA positivity after NAC (if given)/before surgery strongly predicted inoperability and worse survival outcomes, supporting its use for risk stratification. Clinical trial information: UMIN000043561.

Abstract This study validates a methylation-based, tissue-free assay (Latitude TM assay) for detecting molecular residual disease (MRD) in colorectal cancer (CRC), analyzing data from 195 patients (1230 timepoints) from the observational GALAXY study. The assay demonstrated that ctDNA-positivity correlated with significantly worse disease-free survival (DFS) in both the MRD (HR = 10.0, P  < 0.001) and post-definitive treatment surveillance windows (HR = 31.9, P  < 0.001). In the MRD window, the assay demonstrated a sensitivity of 58.5% (38/65), while the specificity in patients who did not receive adjuvant chemotherapy (ACT) was 100% (63/63). Longitudinally, relapse was detected with a sensitivity of 84.4% (54/64), with high specificity at the patient (92.1%; 116/126) and sample (97.2%; 619/637) levels. Median lead time from first circulating tumor DNA (ctDNA)-positive result to relapse was 4.6 months. For high-risk stage II and III CRC, ctDNA-positive patients benefited from ACT (adj.HR = 0.014, P  < 0.0001), unlike ctDNA-negative patients. These findings highlight the robust prognostic and predictive capabilities of this tissue-free MRD assay in CRC patients.

Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring of disease burden. Caris Assure is a multifunctional blood-based assay that couples whole exome and whole transcriptome sequencing on plasma and leukocytes with advanced machine learning techniques to satisfy all three clinical testing needs on one platform. Caris Assure for therapy selection was CLIA validated using 1,910 samples. 376,197 tissue profiles along with 7,061 paired blood and tissue profiles were used to engineer features for three machine learning models. The MCED model was trained on 1,013 patients and validated on an independent set of 2,675 patients. The tissue of origin for MCED model was trained on 1,166 samples and validated using 5-fold cross validation. The MRD & Monitoring model was trained on 3,439 patients and validated on two independent sets of 86 patients for MRD and 101 patients for monitoring. For early detection, sensitivities for stages I-IV cancers (n = 284, 129, 90, 23 respectively) were 83.1%, 86.0%, 84.4%, and 95.7%, all at 99.6% specificity (n = 2149). The diagnostic first-line procedure for tissue of origin was determined for 8 categories with a top-3 accuracy of 85% for stage I and II cancers. Detection of driver mutations for therapy selection from blood collected within 30 days of matched tumor tissue, demonstrated high concordance (PPA of 93.8%, PPV of 96.8%) using CHIP subtraction. For MRD and recurrence monitoring, the disease-free survival of patients whose cancers were predicted to have an event was significantly shorter than those predicted not to have an event using a tumor naïve approach (HR = 33.4, p < 0.005, HR = 4.39, p = 0.008, respectively). The data presented here demonstrate a unified liquid biopsy platform that uses blood-based whole-exome and transcriptome sequencing coupled with artificial intelligence to address the important clinical needs in multi-cancer early detection, monitoring of MRD and recurrent cancers, and precision selection of molecularly targeted therapies.

We study binary Bose-Einstein condensates subject to synthetic magnetic fields in mutually parallel or antiparallel directions. Within the mean-field theory, the two types of fields have been shown to give the same vortex-lattice phase diagram. We develop an improved effective field theory to study properties of collective modes and ground-state intercomponent entanglement. Here, we point out the importance of introducing renormalized coupling constants for coarse-grained densities. We show that the low-energy excitation spectra for the two kindsof fields are related to each other by suitable rescaling using the renormalized constants. By calculating the entanglement entropy, we find that for an intercomponent repulsion (attraction), the two components are more strongly entangled in the case of parallel (antiparallel) fields, in qualitative agreement with recent studies for a quantum (spin) Hall regime. We also find that the entanglement spectrum exhibits an anomalous square-root dispersion relation, which leads to a subleading logarithmic term in the entanglement entropy. All of these are confirmed by numerical calculations based on the Bogoliubov theory with the lowest-Landau-level approximation. Finally, we investigate the effects of quantum fluctuations on the phase diagrams by calculating the correction to the ground-state energy due to zero-point fluctuations in the Bogoliubov theory. We find that the boundaries between rhombic-, square-, and rectangular-lattice phases shift appreciably with a decrease in the filling factor.

The scientific peer-review process is facing a shortage of human resources due to the rapid growth in the number of submitted papers. The use of language models to reduce the human cost of peer review has been actively explored as a potential solution to this challenge. A method has been proposed to evaluate the level of substantiation in scientific reviews in a manner that is interpretable by humans. This method extracts the core components of an argument, claims and evidence, and assesses the level of substantiation based on the proportion of claims supported by evidence. The level of substantiation refers to the extent to which claims are based on objective facts. However, when assessing the level of substantiation, simply detecting the presence or absence of supporting evidence for a claim is insufficient; it is also necessary to accurately assess the logical inference between a claim and its evidence. We propose a new evaluation metric for scientific review comments that assesses the logical inference between claims and evidence. Experimental results show that the proposed method achieves a higher correlation with human scores than conventional methods, indicating its potential to better support the efficiency of the peer-review process.

Spoken dialogue systems (SDSs) utilize automatic speech recognition (ASR) at the front end of their pipeline. The role of ASR in SDSs is to recognize information in user speech related to response generation appropriately. Examining selective listening of humans, which refers to the ability to focus on and listen to important parts of a conversation during the speech, will enable us to identify the ASR capabilities required for SDSs and evaluate them. In this study, we experimentally confirmed selective listening when humans generate dialogue responses by comparing human transcriptions for generating dialogue responses and reference transcriptions. Based on our experimental results, we discuss the possibility of a new ASR evaluation method that leverages human selective listening, which can identify the gap between transcription ability between ASR systems and humans.

Such human-assisting systems as robots need to correctly understand the surrounding situation based on observations and output the required support actions for humans. Language is one of the important channels to communicate with humans, and the robots are required to have the ability to express their understanding and action planning results. In this study, we propose a new task of operative action captioning that estimates and verbalizes the actions to be taken by the system in a human-assisting domain. We constructed a system that outputs a verbal description of a possible operative action that changes the current state to the given target state. We collected a dataset consisting of two images as observations, which express the current state and the state changed by actions, and a caption that describes the actions that change the current state to the target state, by crowdsourcing in daily life situations. Then we constructed a system that estimates operative action by a caption. Since the operative action's caption is expected to contain some state-changing actions, we use scene-graph prediction as an auxiliary task because the events written in the scene graphs correspond to the state changes. Experimental results showed that our system successfully described the operative actions that should be conducted between the current and target states. The auxiliary tasks that predict the scene graphs improved the quality of the estimation results.

Advanced gastric and gastroesophageal junction cancers (GC/GEJCs) harbor diverse molecular signatures, highlighting the need for intricate evaluations to identify potential therapeutic targets. Although whole-transcriptome sequencing (WTS) has emerged as a useful tool for understanding these molecular intricacies, its clinical implications have yet to be fully elucidated. This study evaluated the correlation between immunohistochemistry (IHC) and WTS, compared their clinical significance, and identified potential therapeutic targets undetectable through IHC alone. We enrolled 140 patients with advanced GC/GEJC and assessed them using IHC for six pivotal biomarkers: claudin-18 (CLDN18), human epidermal growth factor receptor 2 (HER2), multiple receptor tyrosine kinases (RTKs), and programmed death ligand 1 (PD-L1). Concurrently, WTS was employed as part of the analyses in MONSTAR-SCREEN-2, a multicenter multiomics study. IHC analysis revealed 16.4% HER2, 39.3% CLDN18 (2+/3 + ≥75%), and 15.8% PD-L1 (combined positive score ≥ 10) positivity, among other molecular markers. Significant correlations were observed between IHC and WTS for all six pivotal biomarkers. Among nineteen HER2 IHC-positive patients treated with anti-HER2 therapeutics, ERBB2 status in WTS was significantly associated with progression-free survival (ERBB2-high vs. -low: median 9.0 vs. 5.6 months, log-rank p = 0.046). IHC-based molecular profiling revealed significantly high expression of CLDN18 in RTK-negative patients, with 78.4% positive for either CLDN18 or PD-L1. Additionally, WTS revealed elevated expression of pivotal biomarkers in patients displaying negative targetable biomarkers via IHC. Our findings highlighted the significant correlation between IHC and WTS, reinforcing the clinical utility of WTS. A subset with IHC-negative but WTS-positive status may benefit from specific biomarker-targeted therapies.

＜文献概要＞ポイント　◆ctDNAによるゲノム解析は,組織生検の侵襲性や空間的・時間的不均一性などを克服し,腫瘍の全体像を包括的に把握しうる.◆ctDNAを用いた臨床開発としては,切除不能例に加え,切除例でも微小残存病変の検出や治療などが進んでいる.◆ctDNA検査は,conversion surgeryの適応や時期の最適化に寄与する可能性がある.

リキッドバイオプシーは液性検体を用いた腫瘍由来の細胞や核酸を解析する技術である。なかでもctDNA解析を用いた技術開発は、近年めざましい進歩を遂げており、ctDNA解析技術を用いた治療開発はコンパニオン診断薬として、すでに実臨床にも用いられている。また、ctDNA解析の特性を生かし、予後予測因子としての観点から新たな治療開発もおこなわれており、非常に注目されている技術である。(著者抄録)

切除不能進行・再発大腸癌は根治が難しく,腫瘍の進行を遅延させ,生存期間を延長することを目的に薬物療法による治療が行われる。殺細胞性抗癌薬や分子標的治療薬,免疫チェックポイント阻害薬を用いた治療開発が行われ,切除不能進行・再発大腸癌における生存期間の延長が得られてきている。本稿ではこれまでの報告を基に,切除不能進行・再発大腸癌に対する薬物療法の変遷や標準治療の最近の進歩,今後の展望について述べる。近年は特定の遺伝子異常に対する個別化をめざした治療開発も進められており,今後のさらなる治療の発展が期待される。(著者抄録)