bluuebunny/crossref_metadata_2025_split huggingface dataset:
HLA class-I antigen presentation machinery (APM) alterations mediate immune evasion in lung cancer brain metastases.
Authors: Vilariño Noelia , Lopez De Rodas Miguel , Ranjan Kishu , Costantini Adrien , Villalba Maria , Lu Benjamin Y. , Kravitz Caro , Nadal Ernest , Goldberg Sarah B. , Nguyen Don , Schalper Kurt A. 
Published: July 2024

e14014 Background: Although ~30% of patients with lung cancer brain metastasis (LBM) achieve intracranial response with immune checkpoint inhibitors (ICI), most have primary resistance, and those who initially respond develop rapid disease progression. The biological factors contributing to this unfavorable clinical scenario are poorly understood and could include distinct immunologic properties of tumors colonizing the brain. Using annotated tumor/patient cohorts, spatially resolved protein analysis, and in vitro models, we investigated the role of HLA class-I APM defects and interferon (IFN)-γ pathway in LBM. Methods: Using multiplex quantitative immunofluorescence, we measured the levels and spatial distribution of HLA class-I APM markers (β2M, tapasin, calreticulin, ERp57, TAP1, and TAP2), IFN-γ signaling (pSTAT1 and IRF-1), and tumor-infiltrating lymphocytes (TILs) (CD8, CD4, and FOXP3) in 56 LBM, 41 primary lung tumors (PLT), and 10 lung-extracranial metastases (ECM) represented in tissue microarrays. A subset of paired LBM/PLT samples from the same patients were also included (n=8). The spatial analysis of the markers was conducted using fluorescence co-localization and single-cell segmentation strategies. Associations between the markers, clinicopathological characteristics, and survival were studied. Protein expression of β2M and IFN-γ-sensitive markers (total STAT1, pSTAT1, IRF1, and PD-L1) before and after treatment with human recombinant IFN-γ was assessed using Western blot in cultured primary lung H2030 adenocarcinoma cells and their in vivo selected brain metastatic counterpart H2030-BrM3. Results: LBM showed significantly lower β2M, TAP2, and tapasin protein levels than PLT. However, LBM also showed higher expression of pSTAT1 and comparable levels of IRF-1 relative to PLT. Similar results were seen in paired LBM/PLT samples, but not in ECM samples. Tumors with low β2M showed reduced CD8+, CD4+, and FOXP3+ TILs. In LBM no significant association between β2M and IFN-γ pathway markers or major clinicopathologic and molecular patient/tumor features were found. LBM samples from patients progressing after radiotherapy and/or chemotherapy showed significantly lower β2M levels. Reduced β2M expression was associated with shorter overall survival in PLT but not in LBM. The brain metastatic H2030-BrM3 cell line showed lower β2M expression both at baseline and after IFN-γ treatment compared with their parental H2030 counterpart. Conclusions: HLA class-I APM downregulation is a prominent feature of LBM, is independent of local adaptive/inducible IFN-γ stimulation, and is associated with unfavorable clinical features. These findings support that HLA class-I APM deficiency plays a major role in immune evasion and immunotherapy resistance in patients with LBM.
Deep learning for 4D modeling of glioblastoma multiforme with tumor treating fields (TTFields) therapy.
Authors: Guerrero Ramirez Andres Felipe , Tang Cynthia Crystal , Kong Xiao-Tang , Bota Daniela Annenelie , Chang Peter D. 
Published: July 2024

e14032 Background: Prediction of future tumor growth and recurrence are critical in the management of patients with glioblastoma multiforme (GBM). This study develops a deep learning method for estimating future areas of GBM spread across multiple timepoints using MRI in patients receiving tumor treating fields (TTFields) therapy. Methods: A single institutional database was queried to identify adult patients with histologically confirmed newly diagnosed and/or recurrent GBM undergoing TTFields therapy. For newly diagnosed GBM, patients received TTFields with temozolomide after maximal debulking surgery and chemoradiation therapy. For recurrent GBM, patients received TTFields as monotherapy. For each patient, all serial follow-up MRI exams were obtained, including T1 (pre-/post-contrast), T2, and T2/FLAIR sequences. On each exam, all regions of enhancing tumor core (excluding peritumoral edema, necrotic core, or resection cavity) were delineated and aligned across time points using nonlinear deformable registration. For any given pair of serial exams, a convolutional neural network (CNN) was designed to predict future GBM tumor on the follow-up exam given the precursor exam and time interval between the studies. The model is implemented as a 3D encoder-decoder architecture yielding a dense per-voxel prediction of future tumor probability optimized using a binary cross-entropy loss function. Class weights were used to develop high sensitivity and high positive predictive value (PPV) model variants. To generate final logit scores, time information is concatenated to the penultimate feature map as an additional feature channel, allowing the model to calibrate each estimate based on elapsed time between any pair of exams. Upon convergence, a 4D learned representation allows for prediction of spatial distribution of GBM tumor at any future time point. Results: A total of 123 patients (1112 total MR exams) were identified. For any given single patient, a median of 6 follow-up exams (IQR 2.5-12.5) at a median interval follow-up time of 46 days (IQR 15.75-63 days) between exams was observed. Upon five-fold cross-validation, the model demonstrated a 0.44 Dice score overlap between predicted and true areas of future GBM tumor growth. The high sensitivity model yielded a per-voxel sensitivity of 0.91 (IQR 0.77-0.99) and PPV of 0.26 (IQR 0.17 to 0.32), while the high PPV model yielded a per-voxel sensitivity of 0.14 (IQR 0.00 to 0.46) and PPV of 0.75 (IQR 0.56 to 0.94). Upon visual confirmation, model predictions across incremental time values for any given exam yielded expected gradual growth of tumor over time. Conclusions: A deep learning model can accurately predict future areas of GBM tumor growth in patients receiving TTFields therapy, with optimal performance that may be calibrated for high sensitivity or high PPV based on clinical use case.
Schwannomas: Experience from a single center reference in Peru.
Authors: Galecio Viera Jianmartin , Paitan Amaro Victor , Castro Oliden Victor 
Published: July 2024

e14043 Background: Schwannomas are nerve sheath tumors that originate in Schwann cells. They are usually solitary and sporadic and manifest on peripheral, spinal or cranial nerves. It is the most common type of benign peripheral nerve tumor in adults. These tumors represent a diagnostic challenge due to their rarity and difficult differential diagnosis. Our objective was to determine the clinical and pathological characteristics, as well as the therapeutic management of patients with Schwannoma admitted to our institution over a period of time. Methods: A retrospective, cross-sectional and descriptive study was carried out on the cases of patients with Schwannoma over 14 years of age, diagnosed at the National Institute of Neoplastic Diseases from 2009 to 2023. Medical records and pathology reports were reviewed. Results: A total of 225 patients were diagnosed with schwannoma on anatomopathology. Median age was 44 years, with a range of 15 to 92 years. 135 (60%) patients were female and 90 (40%) male, with a ratio of 1.5:1. 19 (8.4%) patients had a second cancer before or after the diagnosis of schwannoma. 6 (2.66%) patients were previously diagnosed with neurofibromatosis. According to anatomical origin: 27 (12%) patients had schwanommas of the abdominal region, 36 (16%) of the head and neck, 42 (18.66%) of the spinal cord, 17 (7.55%) of the extremities, 83 ( 36.88%) of the intracranial region and 20 (8.88%) of the thorax. At the intracranial level, 71 patients had location at the cerebellopontine angle, 5 at the orbital level, 2 at the level of the cerebellum and 5 in another location. At the abdominal level, 13 patients had a retroperitoneal location, 8 at the gastric level, 2 at the renal level and 4 in another location. In 130 patients we can obtain the ki67, median score was 2% (1-50%). Regarding treatment, 156 (69.33%) patients underwent surgery, and 42 (18.66%) patients received radiation treatment. During their follow-up, only 5 (2.22%) patients had local recurrence. Conclusions: Schwannomas are rare benign tumors. In many cases, its suspected diagnosis is difficult due to its similarity to other tumors that must be part of the differential diagnosis. Its treatment is surgical, with the objective of complete macroscopic resection. Radiotherapy is a complementary treatment in case of residual disease.
Clinical and molecular mechanisms for predicting the efficacy of immunotherapy for hepatocellular carcinoma based on gut microbiome.
Authors: Zhu Wenwen , Zhang Ningning , Yu Yuexi , Huo Yiming , Lu Wei 
Published: July 2024

e16222 Background: Hepatocellular carcinoma (HCC) is an aggressive malignant tumor, ranking as the fifth most common cancer and the third leading cause of cancer-related deaths globally, posing a significant global health issue. Increasing evidence suggests that the gut microbiome and their metabolites play a crucial role in the development and therapeutic processes of cancer. Immune checkpoint inhibitors (ICIs) have recently become a treatment option for unresectable advanced HCC. To further guide the selection of immunotherapy for clinical HCC patients, it is necessary to further elucidate the prediction of immunotherapy efficacy for HCC based on the microbiome. Methods: The study enrolled 26 unresectable advanced HCC patients and collected baseline clinical laboratory data. We administered ICIs therapy to HCC patients every three weeks. After 6 months of treatment, patients were divided the responsive group (R group) and the non-responsive group (NR group) based on imaging evaluation according to the Response Evaluation Criteria in Solid Tumors (RECIST 1.1). Prior to the application of anti-tumor treatment, fecal samples were collected from the patients for 16S rRNA microbiome sequencing analysis. Immunofluorescence was used to detect the expression of PD-L1 in tumor tissue, and immunohistochemistry was used to assess changes in lymphocyte subsets CD3+T cells, CD4+T cells, CD8+T cells and Treg cells, as well as the expression of TNF-α, γ-IFN, and GZMB. Additionally, the peripheral blood lymphocyte subsets CD3+T cells, CD4+T cells and CD8+T cells were analyzed by flow cytometry. Results: In our study, R group showed higher taxa richness and more gene counts than those of NR group. Comparing with NR group, the relative abundance of Firmicutes were significantly increased, whereas Proteobacteria and Bacteroidota were significantly decreased in R group at phylum level (all P < 0.05). Our study showed that R group had high level of lymphocyte subsets CD3+T cells and CD8+T cells and low level of CD4+T cells and Treg cells compared to NR group (all P < 0.05). And the expressions of PD-L1, TNF-α,γ-IFN and GZMB were upregulated in R group(all P < 0.05). Conclusions: These findings suggested that the characteristics of gut-microbial diversity and composition at the early treatment period of ICIs therapy in HCC may have distinct implications on drug efficacy and disease prognosis. ICIs therapy reshaped HCC tumor microenvironment in parallel with regulating the gut microbiome and lymphocyte subsets immunity.
The efficacy and safety study of thymosin α1 combined with PD-1 antibodies as adjuvant therapy in patients with hepatocellular carcinoma with high-risk recurrence factors after radical resection.
Authors: RongHua Zhu , Zhiyong Huang 
Published: July 2024

e16226 Background: Anti-PD-1 immunotherapy has revolutionized unresectable hepatocellular carcinoma (HCC) treatment. The efficacy of postoperative adjuvant therapy (PAT) using anti-PD-1 in treating HCC is currently the subject of extensive research. This study explored the efficacy and safety of anti-PD-1 antibodies combined with thymosin alpha-1 (Tα1) for patients with HCC and high-risk recurrent factors (HRRFs) post-hepatectomy. Methods: Data from 273 patients with HCC and HRRFs who underwent hepatectomy at Tongji Hospital (January 2019 to July 2022) were prospectively collected. Patients were nonrandomly divided into Tα1+ anti-PD-1 antibodies (65, 23.8%), anti-PD-1 antibodies (84, 30.8%), and control (no adjuvant therapy, 124, 45.4%) groups based on finances and willingness. After propensity score matching (PSM), recurrence-free survival (RFS) and overall survival (OS) were compared. Cox regression analysis identified the RFS- and OS-related prognostic factors, followed by subgroup analysis. Results: After PSM, 65 patients were matched. The anti-PD-1 antibodies + Tα1 group exhibited longer RFS than the anti-PD-1 antibodies (P = 0.014) and control (P < 0.0001) groups. The anti-PD-1 antibodies group had longer RFS than the control group (P < 0.0001). The anti-PD-1 antibodies + Tα1 (P = 0.00049) and anti-PD-1 antibodies groups (P = 0.0041) demonstrated longer OS than the control group. The 1- and 2-year RFS rates in the Tα1 + anti-PD-1 antibodies, anti-PD-1 antibodies, and control groups were 98.4%, 86.2%, and 49.2% (P < 0.001), and 80.2%, 65.8%, and 24.6% (P < 0.001), respectively. The corresponding 1-, 2-, and 3-year OS rates were 100.0%, 100.0%, and 84.6% (P < 0.001), 98.0%, 91.4%, and 69.0% (P < 0.001), and 91.3%, 86.8%, and 57.4% (P < 0.001), respectively. Multivariable analyses suggested that the Tα1 + anti-PD-1 antibodies treatment improved the RFS and OS more than the non-anti-PD-1 antibodies + Tα1 treatment (hazard ratio (HR): 0.174, 95% confidence intervals (CI): 0.089–0.340, P < 0.001 and HR: 0.240, 95% CI: 0.084–0.683, P = 0.008, respectively). Subgroup analysis demonstrated significant RFS and OS benefits for patients with HCC and vascular invasion treated with Tα1 + anti-PD-1 antibodies. Grade 1 and 2 toxicities included rash/pruritus (21.5%), diarrhea (18.5%), and reactive cutaneous capillary endothelial proliferation (RCCEP)(15.4%). Grade 3 toxicities included RCCEP (1.5%), diarrhea (1.5%), rash/pruritus (0.8%), edema (0.8%), hepatitis (0.8%), nausea/vomiting (0.8%), and hypothyroidism (0.8%). No grade 4/5 toxicities or severe adverse events were detected. Conclusions: Combining anti-PD-1 antibodies with Tα1 as adjuvant therapy is safe, improving postoperative prognosis in patients with HCC and HRRFs after hepatectomy, proving more effective than anti-PD-1 antibodies alone.
Adjuvant therapy with donafenib plus anti–PD-1 antibody for patients (pts) with hepatocellular carcinoma (HCC) at high risk of recurrence after resection (PATH study).
Authors: Chen Yiwen , Shen Yan , Zhang Min , Wu Jian , Gao Shunliang , Que Risheng , Yu Jun , Tang Xiaofeng , Bai Xueli , Liang Tingbo 
Published: July 2024

e16228 Background: There is no universally accepted standard treatment option or strategy for post-surgery adjuvant therapy for HCC. Among BCLC A/B patients with MVI, adjuvant TACE provided a 1-year recurrence-free survival rate (RFSR) of around 60-70%. We conducted a pilot study to explore the utility of donafenib combined with anti-PD-1 antibody as adjuvant therapy for pts with high risks of recurrence. Methods: It was planned to enroll 30 HCC pts who had undergone radical surgery and with at least one of the following risk factors: a) Presence of microvascular invasion (MVI); b) Presence of satellite nodule(s); c) > 3 tumor nodules; d) Portal vein tumor thrombus. Pts with invasion of main portal venous were excluded. Donafenib plus anti-PD-1 antibody was initiated at 4 to 8 weeks after resection and continued for up to six months. No other adjuvant therapies were allowed before enrollment and during the study, except for anti-virus treatment. The primary endpoint was the cumulative 1-year RFSR. The secondary endpoints included recurrence-free survival (RFS), overall survival, and safety. Results: From June 2020 to November 2023, a total of 30 pts were recruited. 27 pts were included in efficacy analysis. The mean and median follow-up time was 347.9 days and 179.5 days. The mean and median time from surgery to enrollment was 42.5 days and 42.0 days. MVI was the most common risk factor (Table). Majority of the pts had only one risk factor. Relapse occurred in two pts (7.4%) and RFS was very immature. The RFSR at one year was 89.7% (90% CI, 70.6%-96.7%) in all the evaluable pts, and slightly higher in pts with M1 or only one risk factor (92.9% [90% CI, 68.1%-98.6%] and 93.3% [90% CI, 69.9%-98.7%], respectively). No deaths were observed. In 30 pts who had received at least one dose, the incidence of grade 3 treatment-related adverse events (TRAEs) was 40.0% (12/30). No grade 4 or 5 TRAEs were reported. The grade 3 TRAEs occurred in ≥2 pts were palmar-plantar erythrodysesthesia syndrome (13.3%), rash (13.3%), alanine aminotransferase increased (10.0%), and aspartate aminotransferase increased (6.7%). Conclusions: These results showed that a regimen of 6 months of adjuvant therapy with donafenib plus anti-PD-1 antibody may be efficient to reduce recurrence for BCLC A/B pts at high risk of recurrence, particularly those with ≤2 risk factors. No new safety issues were noticed. Clinical trial information: NCT04418401 . [Table: see text]
Temporal dynamics and prognostic significance of cancer free status in patients with intermediate stage hepatocellular carcinoma: A multicenter cohort study.
Authors: Shen Lujun , Li Chen , Fan Wei-Jun 
Published: July 2024

e16236 Background: A proportion of patients with intermediate stage hepatocellular carcinoma (HCC) can achieve cancer free status (CFS) during treatment, the prognostic value of CFS across the period of dynamic surveillance and treatment remained unknown. Methods: This longitudinal cohort study examined data from the electronic medical record system of four hospitals in China between January 1, 2007 to May 31, 2019. The data from Sun Yat-sen University Cancer Center served as the derivation cohort and other centers as testing cohort. The time-series data were converted into data of time slices, with an interval of three months. Image CFS is defined as patients with no evidence of disease based on imaging exams after treatment and Image-Bio CFS is defined as achievement of Image CFS, together with normal AFP level. Based on the dynamic changes of disease during treatment, patients at specific time slice were classified into either “Arrive”, “Maintain”, or “Not reached” CFS subgroups. The correlations between CFS subgroups and overall survival (OS) were determined by Cox regression. Results: A total of 945 (42.2%) and 741 (33.1%) patients in derivation cohort reached Image CFS and Image-Bio CFS during treatment, respectively. The corresponding rates for Image CFS and Image-Bio CFS in testing cohort were 155 (37.4%) and 130 (31.4%), respectively. Maintaining Image CFS or Image-Bio CFS, rather than just arrive Image CFS or Image-Bio CFS, had stable predictive value for improved OS across different time slices. The merged Hazard ratio of Maintain Image-Bio CFS was 0.23 (95%CI, 0.20-0.25, P < 0.001). The patients achieved Image-Bio CFS could be further classified into three subgroups with differential prognosis based on duration of CFS (≤ 4.5months; 4.5-18.0 months; > 18.0 months). Maintaining Image-Bio CFS for more than 18.0 months predicted long term survival (5-year OS: 91.2% in derivation cohort, 94.7% in testing cohort). Conclusions: Maintaining CFS, rather than just arrive CFS, is a key marker of favorable survival during dynamic management of intermediate stage HCC. A duration of Image-Biochemical CFS for more than eighteen months predicts long-term survival.
Machine learning identification of hypoxia-related genes and prognostic risk-scoring model for effective survival stratification in hepatocellular carcinoma.
Authors: Mohan Huang , Chan Wing Chi 
Published: July 2024

e16261 Background: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality globally, where treatment and prognostic assessment have important implications in clinical practice. Hypoxia, as a common feature within solid tumors, can directly change the tumor microenvironment, which affects the efficacy of cancer treatment and prognosis. In this study, we constructed and validated a hypoxia-based prognostic model using bioinformatics and machine learning. Methods: Two public datasets, GSE14520 and GSE41666, were collected from the Gene Expression Omnibus: (1) HCC tumor tissues compared to adjacent normal tissues (N = 214) and (2) HepG2 cells under normoxic and hypoxic conditions (N = 6). Differential expression analysis was performed to identify HCC characteristic genes and hypoxia-related genes, including their common genes (HCC-Hypoxia Overlap genes, HHOs). Using RNA-seq data of HCC patients (N = 367) from the TCGA Liver Cancer (LIHC) database, univariate Cox regression models were identified, and the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm selected hypoxia-characteristic genes for the multivariate survival model. A hypoxia-related risk score was calculated based on the model of these characteristic genes and dichotomized cases into high-risk (HR) and low-risk (LR) groups. The model was validated using liver cancer cases (N = 232) from the International Cancer Genome Consortium database (ICGC-LIRI-JP). Results: Through differential expression analysis of the two datasets, we identified 52 HHOs. Univariate Cox analysis of these HHOs indicated that 21 genes were significantly associated with HCC patient survival. Through LASSO regression analysis, a total of 9 characteristic genes, including CENPA, KIF20A, DLGAP5, HMMR, UPB1, AFM, CABYR, PHLDA2, and N4BP2L1 were ultimately retained in the survival model. Based on these 9 genes, TCGA-LIHC samples were classified into HR and LR groups, and Kaplan-Meier (KM) analysis revealed significant differences in survival outcomes (p < 0.032). Risk scoring of the ICGC-LIRI-JP validation set classified samples into HR and LR. KM analysis showed that the survival times of patients in the HR group were significantly shorter than those in the LR group (p < 0.0001). Receiver Operating Characteristic Analysis analysis of the survival model showed area under the curve values of 0.815, 0.774, and 0.771 at 1, 2, and 3 years, respectively, demonstrating high performance in risk stratification. Conclusions: This study established a prognostic risk-scoring model based on 9 characteristic genes associated with hypoxia. This model can effectively stratify risks among HCC patients and demonstrate excellent performance in predicting survival. These findings may offer new biomarkers and therapeutic targets for the personalized treatment of HCC.