Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology.

PURPOSE: This study aimed to assess the efficiency of artificial intelligence (AI) in the detection of visceral pleural invasion (VPI) of lung cancer using high-resolution computed tomography (HRCT) images, which is challenging for experts because of its significance in T-classification and lymph node metastasis prediction. METHODS: This retrospective analysis was conducted on preoperative HRCT images of 472 patients with stage I non-small cell lung cancer (NSCLC), focusing on lesions adjacent to the pleura to predict VPI. YOLOv4.0 was utilized for tumor localization, and EfficientNetv2 was applied for VPI prediction with HRCT images meticulously annotated for AI model training and validation. RESULTS: Of the 472 lung cancer cases (500 CT images) studied, the AI algorithm successfully identified tumors, with YOLOv4.0 accurately localizing tumors in 98% of the test images. In the EfficientNet v2-M analysis, the receiver operating characteristic curve exhibited an area under the curve of 0.78. It demonstrated powerful diagnostic performance with a sensitivity, specificity, and precision of 76.4% in VPI prediction. CONCLUSION: AI is a promising tool for improving the diagnostic accuracy of VPI for NSCLC. Furthermore, incorporating AI into the diagnostic workflow is advocated because of its potential to improve the accuracy of preoperative diagnosis and patient outcomes in NSCLC.

AI-driven Characterization of Solid Pulmonary Nodules on CT Imaging for Enhanced Malignancy Prediction in Small-sized Lung Adenocarcinoma.

OBJECTIVES: Distinguishing solid nodules from nodules with ground-glass lesions in lung cancer is a critical diagnostic challenge, especially for tumors ≤2 cm. Human assessment of these nodules is associated with high inter-observer variability, which is why an objective and reliable diagnostic tool is necessary. This study focuses on artificial intelligence (AI) to automatically analyze such tumors and to develop prospective AI systems that can independently differentiate highly malignant nodules. MATERIALS AND METHODS: Our retrospective study analyzed 246 patients who were diagnosed with negative clinical lymph node metastases (cN0) using positron emission tomography-computed tomography (PET/CT) imaging and underwent surgical resection for lung adenocarcinoma. AI detected tumor sizes ≤2 cm in these patients. By utilizing AI to classify these nodules as solid (AI_solid) or non-solid (non-AI_solid) based on confidence scores, we aim to correlate AI determinations with pathological findings, thereby advancing the precision of preoperative assessments. RESULTS: Solid nodules identified by AI with a confidence score ≥0.87 showed significantly higher solid component volumes and proportions in patients with AI_solid than in those with non-AI_solid, with no differences in overall diameter or total volume of the tumors. Among patients with AI_solid, 16% demonstrated lymph node metastasis, and a significant 94% harbored invasive adenocarcinoma. Additionally, 44% were upstaging postoperatively. These AI_solid nodules represented high-grade malignancies. CONCLUSION: In small-sized lung cancer diagnosed as cN0, AI automatically identifies tumors as solid nodules ≤2 cm and evaluates their malignancy preoperatively. The AI classification can inform lymph node assessment necessity in sublobar resections, reflecting metastatic potential.

Omitting Lymph Node Dissection for Small Ground-Glass Opacity-Dominant Tumors.

BACKGROUND: The purpose of this study was to determine the optimal extent of lymph node dissection required in patients with small (≤3 cm) radiologically ground-glass opacity-dominant, peripheral, non-small cell lung cancer tumors. METHODS: The study analyzed the clinicopathologic findings and surgical outcomes of 988 patients with radiologic, ground-glass opacity-dominant non-small cell lung cancer without lymph node involvement who underwent complete resection of the primary tumor between 2010 and 2020. Patients were followed up for 54.5 months (median). Kaplan-Meier curves and the log-rank test were used in statistical analyses of the prognosis. RESULTS: Median age, whole tumor size, solid tumor size, and maximum standardized uptake values were 68 years, 1.7 cm, 0.4 cm, and 0.9, respectively. Sixty percent of the cohort was female (n = 590). Wedge resection, segmentectomy, and lobectomy were performed in 206, 372, and 410 patients, respectively. A total of 982 of 988 (99%) tumors were adenocarcinomas. One patient had hilar lymph node involvement; however, no mediastinal lymph node metastasis or hilar or mediastinal lymph node recurrence was detected. The 5-year overall survival rate was 96.5% (95% CI, 94.8%-97.7%). Excellent survival outcomes were achieved regardless of procedure (wedge resection, 94.7% [95% CI, 89.1%-97.5%]; segmentectomy, 96.9% [95% CI, 93.7%-98.5%]; and lobectomy, 97.1% [95% CI, 94.4%-98.5%]). CONCLUSIONS: Omitting lymph node dissection may be acceptable with curative intent for small tumors with radiologic ground-glass opacity dominance. Appropriate surgical procedures such as wedge resection, segmentectomy, or lobectomy can provide satisfactory outcomes in patients with indolent tumors if surgical margins are secured.

Association between pathological infiltrative tumor growth pattern and prognosis in patients with resected lung squamous cell carcinoma.

INTRODUCTION: Lung squamous cell carcinoma (LUSC) usually shows expansive growth with large tumor nests; few reports on invasive growth patterns (INF) in LUSC have been associated with poor prognosis in gastrointestinal and urothelial cancers. In this study, we examine the association between INF and the prognosis of LUSC. MATERIALS AND METHODS: We analyzed INF as a potential prognostic factor in 254 consecutive patients with LUSC who underwent complete surgical resection at our hospital between 2008 and 2017. INF was classified into 3 categories based on the structure of the tumor other than the large round solid nest of tumor cells. RESULTS: INF was categorized as INFa in 59 patients (23 %) with only well-demarcated large solid tumor cell nests, INFb in 89 patients (35 %) with medium to small, alongside large solid nests, and INFc in 98 patients (39 %) with cord-like/small nests or isolated cells plus large or medium solid nests. No significant lymph node metastasis differences were observed between INFc and INFa/b tumors. However, in patients with p-stage I, INFc had a poorer prognosis with regard to recurrence-free survival (RFS), with a 5-year RFS rate of 53.3 %, compared to 74.9 % for INFa/b (p = 0.010). CONCLUSION: Our study highlights a novel pathological concept of INF in LUSC, and contributed to the proposal that it is a factor indicating an unfavorable prognosis in patients with early-stage LUSC. A prospective multicenter study is warranted for INFc patients, as careful follow-up and adjuvant chemotherapy might lead to the early detection and prevention of recurrence.

Development and validation of an immune-related gene prognostic index for lung adenocarcinoma.

Background: Lung cancer is the most common malignant tumor in the world, and its prognosis is still not optimistic. The aim of this study was to establish an immune-related gene (IRG) prognostic index (IRGPI) for lung adenocarcinoma (LUAD) based on IRGs, and to explore the prognosis, molecular and immune features, and response to immune checkpoint inhibitor (ICI) therapy in IRGPI-classified different subgroups of LUAD. Methods: Based on the LUAD transcriptome RNA-sequencing data in TCGA database, the differentially expressed genes (DEGs) were selected. Subsequently, DEGs were intersected with IRGs to obtain differentially expressed immune-related genes (DEIRGs). Weighted gene co-expression network analysis (WGCNA) identified hub genes in DEIRGs. Finally, univariate and multivariate Cox regression analyses were used to build an IRGPI model. Subsequently, TCGA patients were divided into high- and low-risk groups, and the survival of patients in different groups was further analyzed. Besides, we validated the molecular and immune characteristics, relationship with immune checkpoints, angiogenesis-related genes, and immune subtypes distribution in different subgroups. Meanwhile, we further validated the response to ICI therapy in different subgroups. Results: The IRGPI was constructed based on 13 DEIRGs. Compared with the low-risk group, overall survival (OS) was lower in the high-risk group, and the high-risk score was independently associated with poorer OS. Besides, the high-risk score was associated with cell cycle pathway, high mutation rate of TP53 and KRAS, high infiltration of M0 macrophages, and immunosuppressive state, and these patients had poorer prognosis but the TIDE score of the high-risk group was lower than that of the other group, which means that the high-risk group could benefit more from ICI treatment. In contrast, the low-risk score was related to low mutation rate of TP53 and KRAS, high infiltration of plasma cells, and immunoactive state, and these patients had better prognosis but the low-risk group less benefit from ICI treatment based on the results of TIDE score. Conclusions: IRGPI is a prospective biomarker based on IRGs that can distinguish high- and low-risk groups to predict patient prognosis, help characterize the tumor immune microenvironment, and evaluate the benefit of ICI therapy in LUAD.

Preoperative predictors for recurrence sites associated with poor post-recurrence survival after surgery of non-small cell lung cancer: a multicenter study.

BACKGROUND: The recurrence site that influences post-recurrence survival (PRS) in patients with non-small cell lung cancer (NSCLC) undergoing surgery and the preoperative predictors of recurrence remain unclear. METHODS: Cohorts 1 and 2 had 4520 (who underwent complete resection for p-stage 0-IIIA NSCLC) and 727 (who experienced recurrence after surgery) patients, respectively. The initial sites of recurrence were the lungs (309 cases), thoracic lymph nodes (225 cases), pleura (112 cases), bone (110 cases), central nervous system (86 cases), adrenal gland (25 cases), abdomen (60 cases), cervical and axillary lymph nodes (38 cases), chest wall (13 cases), skin (5 cases), and eye and tongue (3 cases). For cohort 2 analysis, the initial recurrence site that resulted in poor PRS was analyzed by multivariable analysis using a Cox proportional hazard model. For cohort 1 analysis, the preoperative predictors of recurrence patterns with poor PRS were analyzed by multivariable analysis using a logistic regression model. RESULTS: In cohort 2 analysis, recurrence in the central nervous system (hazard ratio [HR], 1.70; p < 0.001), bone (HR, 1.75; p < 0.001), abdomen (HR, 2.39; p < 0.001), and pleura (HR, 1.69; p < 0.001) were independent poor prognostic recurrent sites for PRS and they were high-risk sites (HRS). Intrathoracic lymph nodes, cervical and axillary lymph nodes, lungs, chest wall, adrenal gland, eye and tongue, and skin were low-risk sites (LRS) that did not affect PRS. Patients with multiple LRS without HRS recurrence had a worse prognosis than those with a single LRS without HRS recurrence (5-year PRS 20.2% vs. 37.7%, p < 0.001) and were comparable to those with HRS recurrence (p = 1.000). In cohort 1 analysis, preoperative predictors for HRS and multiple LRS recurrences were positron emission tomography (PET) maximum standardized uptake value (maxSUV) ≥ 3.2 (HR, 5.09; p < 0.001), clinical nodal metastasis (HR, 2.00; p < 0.001), tumor size ≥ 2.4 cm (HR, 1.96; p < 0.001) and carcinoembryonic antigen (CEA) ≥ 5 ng/ml (HR, 1.41; p = 0.004). The cumulative incidence rates of HRS and multiple LRS recurrences within 5 years were 55.9%, 40.9%, 26.3%, 11.1%, and 3.5% (p < 0.001) in patients with 4, 3, 2, 1 and 0 of the above risks, respectively. CONCLUSIONS: HRS and multiple LRS were vital recurrences associated with poor PRS. Preoperative PET maxSUV, clinical nodal metastasis, tumor size, and CEA level predicted the incidence of vital recurrence.

Sublobar resection utilizing near-infrared thoracoscopy with intravenous indocyanine green for intralobar pulmonary sequestration: a case report and literature review.

BACKGROUND: Pulmonary sequestration is a rare pulmonary malformation, with intralobar pulmonary sequestration being the most common subtype. Lobectomy has generally been performed for its treatment, owing to unclear boundaries of the lesion. However, recent reports have introduced lung resection using intravenous indocyanine green (ICG) as a treatment for pulmonary sequestrations. CASE DESCRIPTION: A 34-year-old woman presented with chest pain, and enhanced chest computed tomography (CT) displayed a solid mass of 4.5 × 3.1 cm in the right S10 area. An aberrant artery was found running from the celiac artery through the diaphragm to the thoracic cavity. The patient was diagnosed as having pulmonary sequestration Pryce type III, and surgical resection was performed. Intrathoracic findings demonstrated that the precise area of the pulmonary sequestration could not be clearly identified, and a 5-mm aberrant artery was present in the pulmonary ligament. Following the separation of the aberrant artery, intravenous injection of ICG clearly delineated the border between the normal lung tissue and the pulmonary sequestration. Wedge resection was then performed without any postoperative events, and the pathological diagnosis was also pulmonary sequestration. CONCLUSIONS: We herein reported a case of a patient who underwent sublobar resection for intrapulmonary sequestration using intravenous ICG injection, together with a literature review. Our case suggests that a comprehensive understanding of abnormal vessels and pulmonary vasculature in pulmonary resection for intrapulmonary sequestrations, complemented with the use of ICG, might potentially avoid unnecessary pulmonary resection and enable sublobar surgical resection.

Wedge resection vs. segmentectomy for lung cancer measuring ≤ 2 cm with consolidation tumor ratio > 0.25.

Objectives: We aimed to clarify the differences in prognosis between wedge resection and segmentectomy performed for cN0 non-small cell lung cancer (NSCLC) measuring ≤ 2 cm, with consolidation tumor ratio (CTR) > 0.25. Methods: This multicenter study included 570 patients with cN0 NSCLC (tumor size ≤ 2 cm, CTR > 0.25) who underwent wedge resection (n = 244) and segmentectomy (n = 326) between January 2010 and December 2018. After propensity score matching (PSM, 1:1 method), 182 patients were matched for clinical characteristics (age, sex, laterality, smoking index, tumor size, CTR, carcinoembryonic antigen value, positron-emission tomography-documented maximum standardized uptake value, clinical stage, and tumor disappearance rate) and intergroup comparison of disease-free survival (DFS) and overall survival (OS). Using Gray's test, an intergroup comparison of the cumulative incidence of lung cancer-specific mortality was performed. Results: After PSM, similar DFS (5-year DFS, 79.9% vs. 87.1%, p = 0.103) and OS (5-year OS, 88.7% vs. 88.9%, p = 0.719) rates were observed in the wedge resection and segmentectomy groups. We observed no significant intergroup differences in lung cancer-specific mortality (5-year cumulative incidence: 4.6% vs. 3.5%; p = 0.235). Subgroup analysis revealed no specific subgroup demonstrating improved DFS or OS after undergoing wedge resection or segmentectomy. Conclusion: DFS, OS, and lung cancer-specific mortality were comparable between wedge resection and segmentectomy of cN0 NSCLC-tumor size ≤ 2 cm and CTR > 0.25. Large-scale prospective clinical trials are warranted to compare the prognoses of wedge resection and segmentectomy for these tumors.

Extracellular vesicle-associated microRNA signatures related to lymphovascular invasion in early-stage lung adenocarcinoma.

Lymphovascular invasion (LVI) is a fundamental step toward the spread of cancer. Extracellular vesicles (EVs) promote cellular communication by shuttling cargo, such as microRNAs (miRNAs). However, whether EV-associated miRNAs serve as biomarkers for LVI remains unclear. This study aimed to identify EV-associated miRNAs related to LVI and validate the miRNA levels from patients with early-stage lung adenocarcinoma (LADC). Blood samples were collected from patients undergoing pulmonary resection for stage I LADC before surgery. The patients were classified into three groups according to the presence of LVI and postoperative recurrence. Serum-derived EVs in the derivation cohort were used for small RNA sequencing, while the selected LVI miRNA candidates were validated via real-time quantitative polymerase chain reaction using 44 patient and 16 healthy donor samples as the validation cohorts. Five miRNAs (miR-99b-3p, miR-26a-5p, miR-93-5p, miR-30d-5p, and miR-365b-3p) were assessed, and miR-30d-5p (p = 0.036) levels were significantly downregulated in the LVI-positive group. miR-30d-5p levels in healthy donors were lower than those in LADC patients. Patients with high miR-30d-5p levels had favorable survival compared to those with low miR-30d-5p levels. miR-30d-5p level in EVs may serve as a promising biomarker for detecting LVI in patients with early-stage LADC.

[Digital Innovation for Lung Segmentectomy for Early-stage Small Lung Cancer].

In recent years, the number of cases of small-size lung cancer(<2 cm) has increased with the widespread of computed tomography (CT) in medical checkup and comprehensive medical checkup. Although lobectomy has been the standard surgical treatment for early-stage small-size lung cancer, it has become possible to evaluate the CT findings of small tumors in terms of ground-glass areas and solid areas, and it has become clear that the former has a low histological malignancy while the latter has a high malignancy. Lung cancers with high ground-glass opacity have low malignant potential and are therefore being aggressively treated by limited resection. The number of lung segmentectomies is expected to increase in the future, and accurate identification of pulmonary intersegmental planes is important in this operation. Especially in thoracoscopic surgery, where the field of view and surgical operation are limited, tumor localization and intersegmental planes identification are particularly important and require preoperative and intraoperative planning. In order to perform safe and reliable lung segmentectomy, we create a three-dimensional (3D) lung model by Synapse Vincent for preoperative simulation of pulmonary vascular, tumor location, and intersegmental plane. In addition, preoperative simulations are performed using wearable goggles to freely move the 3D lung model in a virtual reality (VR) space. Intraoperatively, in addition to indocyanine green (ICG)-based intersegmental identification, digital assistance is used for tumor and intersegmental identification using mixed reality( MR) goggles. We describe the current status and future prospects of segmentectomy in our institution.

Artificial intelligence-based radiomics for the prediction of nodal metastasis in early-stage lung cancer.

We aimed to investigate the value of computed tomography (CT)-based radiomics with artificial intelligence (AI) in predicting pathological lymph node metastasis (pN) in patients with clinical stage 0-IA non-small cell lung cancer (c-stage 0-IA NSCLC). This study enrolled 720 patients who underwent complete surgical resection for c-stage 0-IA NSCLC, and were assigned to the derivation and validation cohorts. Using the AI software Beta Version (Fujifilm Corporation, Japan), 39 AI imaging factors, including 17 factors from the AI ground-glass nodule analysis and 22 radiomics features from nodule characterization analysis, were extracted to identify factors associated with pN. Multivariate analysis showed that clinical stage IA3 (p = 0.028), solid-part size (p < 0.001), and average solid CT value (p = 0.033) were independently associated with pN. The receiver operating characteristic analysis showed that the area under the curve and optimal cut-off values of the average solid CT value relevant to pN were 0.761 and -103 Hounsfield units, and the threshold provided sensitivity, specificity, and negative predictive values of 69%, 65%, and 94% in the entire cohort, respectively. Measuring the average solid-CT value of tumors for pN may have broad applications such as guiding individualized surgical approaches and postoperative treatment.

Clinical utility of psoas muscle volume in assessment of sarcopenia in patients with early-stage non-small cell lung cancer.

PURPOSE: Sarcopenia influences postoperative outcomes of patients with non-small cell lung cancer (NSCLC). Imaging tools for evaluating and diagnosing sarcopenia have developed, and a novel method of psoas volume index (PVI) obtained by measuring bilateral psoas major muscle volume has been reported. However, the relationship between sarcopenia based on PVI and clinical outcomes has not been fully investigated for patients with early-stage NSCLC. This study aimed to clarify the utility of PVI values in assessing the relationshipe between sarcopenia and clinical outcomes. METHODS: This study included 645 patients with stage I-II NSCLC who underwent curative lung resection between 2012 and 2017. Bilateral psoas major muscle volumes were calculated semi-automatically using a three-dimensional workstation. The cutoff value of PVI for defining sarcopenia was < 60.5 cm3/m3 for men and < 43.6 cm3/m3 for women. RESULTS: The avrage time to obtaine PVI was only 25 s with the 3D system, and interobserver agreements for evauating sarcopenia on PVI was 1. A total of 159 patients (24.7%) were preoperatively diagnosed with sarcopenia. On multivariate analysis, sarcopenia was an independent prognostic factor for overall survival (OS, p < 0.001), recurrence-free survival (RFS, p < 0.001), and lung cancer-specific survival (LCS, p < 0.001). The 5-year OS, RFS, and LCS were significantly worse in sarcopenic patients than non-sarcopenic patients (88.8 vs. 72.4%, p < 0.001; 80.1 vs. 65.0%, p < 0.001; 92.4 vs. 78.9%, p < 0.001, respectively). CONCLUSION: Sarcopenia diagnosed using PVI is an independent prognostic predictor of OS, RFS, and LCS in early-stage NSCLC.

Radiomics with Artificial Intelligence for the Prediction of Early Recurrence in Patients with Clinical Stage IA Lung Cancer.

BACKGROUND: We seek to explore the ability of computed tomography (CT)-based radiomics coupled with artificial intelligence (AI) to predict early recurrence (< 2 years after surgery) in patients with clinical stage 0-IA non-small cell lung cancer (c-stage 0-IA NSCLC). PATIENTS AND METHODS: Data of 642 patients were collected for early recurrence and assigned to the derivation and validation cohorts at a ratio of 2:1. Using the AI software Beta Version (Fujifilm Corporation, Japan), 39 AI imaging factors, including 17 factors from the AI ground-glass nodule analysis and 22 radiomic features from nodule characterization analysis, were extracted. RESULTS: Multivariate analysis showed that male sex (p = 0.016), solid part size (p < 0.001), CT value standard deviation (p = 0.038), solid part volume ratio (p = 0.016), and bronchus translucency (p = 0.007) were associated with recurrence-free survival (RFS). Receiver operating characteristics analysis showed that the area under the curve and optimal cutoff values relevant to recurrence were 0.707 and 1.49 cm for solid part size, and 0.710 and 22.9% for solid part volume ratio, respectively. The 5-year RFS rates for patients in the validation set with solid part size ≤ 1.49 cm and > 1.49 cm were 92.2% and 70.4% (p < 0.001), whereas those for patients with solid part volume ratios ≤ 22.9% and > 22.9% were 97.8% and 71.7% (p < 0.001), respectively. CONCLUSIONS: CT-based radiomics coupled with AI contributes to the noninvasive prediction of early recurrence in patients with c-stage 0-IA NSCLC.

Clinical Impact of Sarcopenia 1 Year After Surgery for Patients with Early-Stage Non-small Cell Lung Cancer.

BACKGROUND: Sarcopenia is associated with prognostic outcomes for patients with various solid tumors, whereas the clinical significance of sarcopenia 1 year after surgery (post-sarcopenia) for non-small cell lung cancer (NSCLC) has not been investigated. This study aimed to clarify the clinical impact of post-sarcopenia and factors associated with post-sarcopenia in NSCLC patients without preoperative sarcopenia. METHODS: This study enrolled 443 patients with clinical stage 1 or 2 NSCLC (234 patients without preoperative sarcopenia [NS group] and 209 patients with preoperative sarcopenia [S group]) who underwent computed tomography (CT) at two time points (before surgery and a year afterward) or more. The study assessed CT images at the L3 level to calculate the psoas muscle area index (PAI). The PAI cutoff value for sarcopenia was defined as 6.36 cm2/m2 for the men and 3.92 cm2/m2 for the women. RESULTS: In the NS group, the diagnosis for 40.1% of the women and 52.6% of the men was post-sarcopenia (NS-S group). The overall survival (OS) for the S and NS-S cohorts was worse than for the non-sarcopenic patients before and after surgery (p < 0.001 and p = 0.017, respectively). In the multivariable analysis, sarcopenia, either before or after surgery (hazard ratio, 3.272; p = 0.002), in the NS group was independently associated with OS, whereas the factors associated with post-sarcopenia were male sex (p = 0.002), aging (p < 0.001), and low body mass index (p < 0.001). CONCLUSIONS: Sarcopenia, either before or after surgery, is prognostic in early-stage NSCLC. Male sex, aging, and low body mass index (BMI) are associated with post-sarcopenia.

Prognostic impact of artificial intelligence-based volumetric quantification of the solid part of the tumor in clinical stage 0-I adenocarcinoma.

INTRODUCTION: The size of the solid part of a tumor, as measured using thin-section computed tomography, can help predict disease prognosis in patients with early-stage lung cancer. Although three-dimensional volumetric analysis may be more useful than two-dimensional evaluation, measuring the solid part of some lesions is difficult using this methods. We developed an artificial intelligence-based analysis software that can distinguish the solid and non-solid parts (ground-grass opacity). This software calculates the solid part volume in a totally automated and reproducible manner. The predictive performance of the artificial intelligence software was evaluated in terms of survival or recurrence-free survival. METHODS: We analyzed the high-resolution computed tomography images of the primary lesion in 772 consecutive patients with clinical stage 0-I adenocarcinoma. We performed automated measurement of the solid part volume using an artificial intelligence-based algorithm in collaboration with FUJIFILM Corporation. The solid part size, the solid part volume based on traditional three-dimensional volumetric analysis, and the solid part volume based on artificial intelligence were compared. RESULTS: Higher areas under the curve related to the solid part volume were provided by the artificial intelligence-based method (0.752) than by the solid part size (0.722) and traditional three-dimensional volumetric analysis-based method (0.723). Multivariate analysis demonstrated that the solid part volume based on artificial intelligence was independently correlated with overall survival (P = 0.019) and recurrence-free survival (P < 0.001). CONCLUSION: The solid part volume measured by artificial intelligence was superior to conventional methods in predicting the prognosis of clinical stage 0-I adenocarcinoma.

Efficacy of Adjuvant Chemotherapy With Tegafur-Uracil in Patients With Completely Resected, Node-Negative NSCLC-Real-World Data in the Era of Molecularly Targeted Agents and Immunotherapy.

Introduction: In Japan, adjuvant tegafur-uracil (UFT) chemotherapy is recommended for patients with completely resected, stage I NSCLC. This treatment requires real-world re-evaluation because of recent advances in target-based and immuno-oncological treatments and refinement of lung cancer staging. Methods: The Japan Clinical Oncology Group (JCOG) 0707, a phase 3 trial comparing the benefits of UFT and S-1 (tegafur-gimeracil-oteracil) in patients with completely resected stage I NSCLC (T1 >2 cm and T2 in the TNM sixth edition), was conducted in Japan. A multicenter observational cohort study (Comprehensive Support Project for Oncology Research [CSPOR]-LC03) was also conducted for those patients excluded from JCOG 0707 during the study enrollment period. Physicians from institutions that participated in JCOG 0707 retrospectively assessed the medical records of each patient. The efficacy of UFT was evaluated in the CSPOR-LC03 cohort. Results: In the entire study population (n = 5005), patients treated with UFT (n = 1549) had significantly longer overall survival (OS) than those without any adjuvant chemotherapy (n = 3338). There was no significant difference in OS between the patients treated with UFT (n = 1061) and those without adjuvant chemotherapy (n = 1484) in the JCOG 0707-eligible population (logrank p = 0.755). For tumors without ground-glass attenuation and size greater than 3 cm, patients treated with UFT had significantly longer survival than those without adjuvant chemotherapy, on univariate but not on multivariate analysis. Conclusions: There was no significant difference in OS between the patients treated with UFT and those without adjuvant chemotherapy in the clinical trial-eligible population. Adjuvant UFT for patients with completely resected NSCLC may be recommended only in patients with a tumor without ground-glass attenuation and size greater than 3 cm. In patients with node-negative early NSCLC, further study is needed to select patients who will benefit from adjuvant chemotherapy.

Nuclear microRNAs release paused Pol II via the DDX21-CDK9 complex.

RNA activation (RNAa) is an uncharacterized mechanism of transcriptional activation mediated by small RNAs, such as microRNAs (miRNAs). A critical issue in RNAa research is that it is difficult to distinguish between changes in gene expression caused indirectly by post-transcriptional regulation and direct induction of gene expression by RNAa. Therefore, in this study, we seek to identify a key factor involved in RNAa, using the induction of ZMYND10 by miR-34a as a system to evaluate RNAa. We identify the positive transcription elongation factors CDK9 and DDX21, which form a complex with nuclear AGO and TNRC6A, as important transcriptional activators of RNAa. In addition, we find that inhibition of DDX21 suppresses RNAa by miR-34a and other miRNAs without inhibiting post-transcriptional regulation. Our findings reveal a strong connection between RNAa and release of paused Pol II, facilitating RNAa research by making it possible to separately analyze post-transcriptional regulation and RNAa.