tbuckley/cabot-search huggingface dataset:
Abstract 6531: Anti-tumor immune function of NR2F6, an orphan nuclear receptor, in stromal cells
Authors: Hyungsoo Kim, Yongmei Feng, Marria Radaeva, Eduard Sergienko, Artem Cherkasov, Ze'ev A. Ronai
Journal: Cancer Research (2024)

Abstract Growing evidence points to the importance of the tumor microenvironment (TME) in tumor growth control, progression, and therapy response. Among those is the greater understanding of immune system components within the TME as mediators of tumor growth control. NR2F6 is an orphan nuclear receptor, which was shown to serve as an immune intrinsic checkpoint component and has been suggested to elicit tumor-intrinsic suppression of anti-tumor immunity. Correspondingly, genetic depletion of NR2F6 in CD8 T cells abrogates the immune-activating cytokines (e.g., IL-2, IFNg). In addition, genetic ablation of NR2F6 in melanoma cells activates CD8 T cell-mediated anti-tumor immunity partly by suppressing the expression of tumor-intrinsic immune repressors NACC1 and FKBP10. Notably, combined genetic ablation of tumor cells (NR2F6 KO melanoma) and stroma cells (NR2F6 KO mouse) resulted in a more pronounced inhibition of tumor growth compared with ablation of either tumor cells or TME. The latter provides the foundation for screening NR2F6 inhibitors, which are expected to have a strong systemic (tumor inhibition and immune cell activation) effect on tumor growth. Interestingly, single-cell transcriptomic data from human tumors identified high expression of NR2F6 in stroma cells, cancer-associated fibroblasts (CAFs), and tumor-associated endothelial cells (TAEs). Consistent with these, scRNAseq analysis of mouse melanoma revealed higher expression of NR2F6 in SMA+ immune suppressive myo-CAFs than in immune activating CAFs. Studies that directly reveal the role of stromal NR2F6 in anti-tumor immunity and tumor growth and the state of NR2F6 inhibitors will be discussed. Citation Format: Hyungsoo Kim, Yongmei Feng, Marria Radaeva, Eduard Sergienko, Artem Cherkasov, Ze'ev A. Ronai. Anti-tumor immune function of NR2F6, an orphan nuclear receptor, in stromal cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6531.
Abstract 7651: Evaluating epigenetic markers for naive, memory and overall B cells for disease diagnosis and prognosis in patients with B-CLL
Authors: Konstantin Schildknecht, Kati Bourquain, Jeannette Werner, Janika Schulze, Steffi Walter, Eva Raschke, Deborah Phippard, Angelina Bisconte, Barbara Seliger, Claudia Wickenhauser, Sven Olek
Journal: Cancer Research (2024)

Abstract Chronic lymphocytic leukemia (CLL) is a hematological cancer classified as low-malignancy non-Hodgkin lymphoma that accounts for approximately a quarter of all leukemias. Since only some patients will develop aggressive cancer and require treatment, accurate disease prognosis is crucial. A wide range of parameters with prognostic value have been described, including age, clinical stage, mutational status, protein markers, and flow cytometry levels of CD19+CD38+ B cells above 20%. Here, we investigated epigenetic markers for B cell types including a marker for overall B cells, naïve B cells, memory B cells and IgM positive B cells in a cohort of more than 40 patients with B-CLL. When comparing to a cohort of more than 100 healthy donors, the epigenetic B cell marker identified all patients with 100% sensitivity and specificity. In addition, the epigenetic B cell markers for naïve and memory B cells identified with high sensitivity and excellent specificity a subgroup of B-CLL patients with CD19+CD38+ B cell levels above 20% which is associated with an unfavorable prognosis. The results suggest that the epigenetic analysis of B cells in capillary blood may be a promising tool for B-CLL diagnosis and disease prognosis. Citation Format: Konstantin Schildknecht, Kati Bourquain, Jeannette Werner, Janika Schulze, Steffi Walter, Eva Raschke, Deborah Phippard, Angelina Bisconte, Barbara Seliger, Claudia Wickenhauser, Sven Olek. Evaluating epigenetic markers for naive, memory and overall B cells for disease diagnosis and prognosis in patients with B-CLL [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7651.
Abstract 7648: COL6A1 expression as a potential prognostic biomarker for risk stratification of T1HG bladder cancer: Unveiling the aggressive nature of a distinct non-muscle invasive subtype
Authors: Xuan-Mei Piao, Young Joon Byun, Chuang-Ming Zheng, Seon-Kyu Kim, Seong-Hwan Park, Kyungchan Min, Hansoo Park, Sungmin Moon, Kyeong Kim, Ho Won Kang, Won Tae Kim, Seok Joong Yun
Journal: Cancer Research (2024)

Abstract Introduction and Objectives: T1 high grade (T1HG) bladder cancer (BC) is a type of non-muscle invasive BC (NMIBC) that is recognized as an aggressive subtype with a heightened propensity for progression. Current risk stratification methods for NMIBC rely on clinicopathological indicators; however, these approaches do not adequately capture the aggressive nature of T1HG BC. Thus, new, more accurate biomarkers for T1HG risk stratification are needed. Here, we enrolled three different patient cohorts and investigated expression of COL6A1, a key component of the extracellular matrix, at different stages and grades of BC, with a specific focus on T1HG BC. Materials and Methods: Samples from 298 BC patients were subjected to RNA sequencing and real-time PCR. Results: We found that T1HG BC and muscle invasive BC (MIBC) exhibited comparable expression of COL6A1, which was significantly higher than that by other NMIBC subtypes. In particular, T1HG patients who later progressed to MIBC had considerably higher expression of COL6A1 than Ta, T1 low-grade patients, and patients that did not progress, highlighting the aggressive nature and higher risk of progression associated with T1HG BC. Moreover, Cox and Kaplan-Meier survival analyses revealed a significant association between elevated expression of COL6A1 and poor progression-free survival of T1HG BC patients (multivariate Cox hazard ratio, 16.812; 95% confidence interval, 3.283-86.095; P=0.001 and P=0.0002 [log-rank test]). Conclusion: These findings suggest that COL6A1 may be a promising biomarker for risk stratification of T1HG BC, offering valuable insight into disease prognosis and guidance of personalized treatment decisions. Citation Format: Xuan-Mei Piao, Young Joon Byun, Chuang-Ming Zheng, Seon-Kyu Kim, Seong-Hwan Park, Kyungchan Min, Hansoo Park, Sungmin Moon, Kyeong Kim, Ho Won Kang, Won Tae Kim, Seok Joong Yun. COL6A1 expression as a potential prognostic biomarker for risk stratification of T1HG bladder cancer: Unveiling the aggressive nature of a distinct non-muscle invasive subtype [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7648.
Abstract 6543: A map of osteosarcoma cell architecture reveals convergence of pediatric cancer mutations on protein assemblies
Authors: Mengzhou Hu, Leah V. Schaffer, Edward L. Huttlin, Gege Qian, Andrew Latham, Abantika Pal, Laura Pontano Vaites, Trang Le, Yue Qin, Christopher Churas, Dexter Pratt, Robin Bachelder, Peter Zage, Ignacia Echeverria, Andrej Šali, J. Wade Harper, Steven P. Gygi, Emma Lundberg, Trey Ideker
Journal: Cancer Research (2024)

Abstract Pediatric tumors are characterized by a low incidence of somatic mutations, which occur in different genomic patterns from adult cancers. For these reasons, interpreting the functional impact of mutations in pediatric cancer patients has remained difficult. One approach to interpreting rare coding mutations is to analyze the convergence of these mutations on larger structural and functional units, such as protein complexes, super assemblies, biomolecular condensates, and organelles. Towards this aim, we created a cancer cell map in the osteosarcoma cell line based on proteome-wide integration of protein interactions and immunofluorescent imaging in U-2 OS pediatric bone cancer cells. This multiscale integrated cell map of U-2 OS cell organizes 5,254 proteins into 270 protein assemblies. Using this multiscale cell map, we analyze 772 genomes from 18 cancer types reported in the DKFZ pan-pediatric cancer study to identify 25 protein assemblies in the map under mutational pressure. This analysis reveals mutated protein assemblies involved with chromatin maintenance and remodeling as well as cell integrity and mobility. For example, we identify a Collagen Biosynthesis and Remodeling Complex, as mutated in 9 cancer types and 15 patients in the dataset, indicating extracellular matrix remodeling is associated with pediatric cancer progression. We also identify a putative biological condensate, which we call the Nuclear Transcription Suppression Complex (NTSC). This protein assembly is found mutated in 20 patients across 10 cancer types, implicating intrinsically disordered proteins in development of pediatric cancer. Overall, this work illustrates how a global multiscale map of cell architecture enables a mechanistic understanding of clinical patient genomes. Citation Format: Mengzhou Hu, Leah V. Schaffer, Edward L. Huttlin, Gege Qian, Andrew Latham, Abantika Pal, Laura Pontano Vaites, Trang Le, Yue Qin, Christopher Churas, Dexter Pratt, Robin Bachelder, Peter Zage, Ignacia Echeverria, Andrej Šali, J. Wade Harper, Steven P. Gygi, Emma Lundberg, Trey Ideker. A map of osteosarcoma cell architecture reveals convergence of pediatric cancer mutations on protein assemblies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6543.
Abstract 7650: An analysis of the prognostic role of sarcopenia derived with fully automated deep learning slice-based muscle estimation in patients with metastatic non-small cell lung cancer (NSCLC)
Authors: Wiem Safta, Rafael Santana-Davila, David Paulucci, William J. Geese, Diederik J. Grootendorst
Journal: Cancer Research (2024)

Abstract Introduction: Sarcopenia, progressive and generalized loss of skeletal muscle mass, is difficult and labor intensive to directly measure as it requires manual segmentations by radiologists from computed tomography (CT) scans. Sarcopenia has been shown to be a prognostic factor in some metastatic cancers. We evaluated the impact of sarcopenia derived via an automated segmentation algorithm on outcomes in the Phase 3 NSCLC clinical trial, CheckMate 227 (NCT02477826) Methods: The sarcopenia score assessment involves automated selection of the L3 vertebra level slice from abdominal or chest, abdomen, and pelvis (CAP) CT scans, followed by automated segmentation of the muscle area from that slice. Sarcopenia scores were derived from previously established definitions of sarcopenia, with values below 41 cm2/m2 for female patients (regardless of BMI) and below 43 cm2/m2 or 53 cm2/m2 for male (based on BMI &amp;lt; 25 kg/m2 or ≥ 25 kg/m2). Among the 967 patients with evaluable scans, sarcopenia at baseline was identified in 68.39% (n=329/481) patients receiving nivolumab (NIVO) with ipilimumab (IPI) and 70.2% (n=341/486) receiving chemotherapy (Chemo). Results: There was a trend of worse overall survival (OS) in patients with baseline sarcopenia across both treatment arms (minimum follow up 49.4 months). In patients with baseline sarcopenia vs ITT, median OS was 16.5 mo vs. 21.8 mo (p= 0.219) within the NIVO + IPI arm and 12.9 mo vs.15.0 mo (p= 0.273) within the Chemo arm respectively. Any increase in muscle mass from baseline to week 12 was associated with better OS for patients treated with NIVO+IPI (n=98) with sarcopenia at baseline compared to those without an increase in muscle mass (median OS 45.3 mo vs.19.5 mo, p= 0.012). This was not seen in those who received Chemo (n=87). Weight and muscle mass were moderately correlated at baseline (r=0.60). Conclusions: We found that in CheckMate 227, baseline sarcopenia is associated with numerically worse OS, regardless of treatment, leading to potential use as a negative prognostic biomarker. Patients with NSCLC receiving immunotherapy might benefit from changes in muscle mass being monitored during treatment. Validation of these findings in other studies and other tumor types is warranted. Citation Format: Wiem Safta, Rafael Santana-Davila, David Paulucci, William J. Geese, Diederik J. Grootendorst. An analysis of the prognostic role of sarcopenia derived with fully automated deep learning slice-based muscle estimation in patients with metastatic non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7650.
Abstract 4997: Auranofin enhances the efficacy of anti-PD1 immunotherapy
Authors: Zichen Zhao, Shichuan Hu, Yan Zhang
Journal: Cancer Research (2024)

Abstract Anti-PD-1 immunotherapy brings hope for the treatment of malignant tumors, but its overall response rate is low. Therefore, how to sensitize anti-PD-1 therapy to make more patients benefit from immunotherapy is an urgent clinical demand. PKCι, a classical oncogene that affects cell proliferation and differentiation, has recently been found to be involved in the recruitment of immunosuppressive cells MDSCs and Tregs, which leads to anti-PD1 immunotherapy resistance. Our study is consistent with previously reported results that interfering with PKCι expression in tumor cells significantly enhances the anti-tumor effect of anti-PD1 therapy. Immunological mechanistic analyses demonstrated that the inhibition of PKCι expression significantly reduced the infiltration of tumor-associated macrophages (TAMs) rather than MDSCs or Tregs. Further studies revealed that PKCι enhanced the expression of macrophage chemokine CCL7 by promoting the formation of the YAP1/TEAD transcriptional complex. Interference in vitro and pharmacological inhibition of PKCι in tumor cells both significantly reduced CCL7 expression and TAMs invasion. Auranofin is a commonly used anti-inflammatory agent in clinical practice, which has been recently found that it directly induces tumor death by modulating the cellular redox system in tumor cells and remodels the tumor immunosuppressive microenvironment by specifically inhibiting PKCι expression. The results of our study showed that the anti-tumor effect of Auranofin combined with anti-PD1 therapy was superior to that of monotherapy in lung adenocarcinoma. Auranofin exerted synergistic anti-tumor effects with anti-PD1 immunotherapy by inhibiting the expression of PKCι-YAP1/TEAD-CCL7, reducing the recruitment of TAMs, and promoting the infiltration of effector CD8+ T cells. In summary, Auranofin is a potent candidate for sensitizing anti-PD-1 immunotherapy, reversing immunotherapy blunting by remodeling TIME, which provides new ideas and theoretical basis for immunotherapy of sensitizing malignant tumors. Citation Format: Zichen Zhao, Shichuan Hu, Yan Zhang. Auranofin enhances the efficacy of anti-PD1 immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4997.
Abstract 4965: Detection of status of cancer in radiology notes using artificial intelligence
Authors: Ankur Arya, Andrew Niederhausern, Nadia S. Bahadur, Neil J. Shah, Chelsea Nichols, Avijit Chatterjee, John Philip
Journal: Cancer Research (2024)

Abstract Introductory Statement: The goal is to use an AI model to replicate the human curator’s response on cancer status in radiology notes of ~20,000 cancer patients. Introduction: MSKCC currently has ~100,000 patients with genomic testing (IMPACT) and continues to accrue more. Clinicians use this genomic data for research but lack clinical structured data to analyze alongside the genomic data. We use a vendor called VASTA Global to manually curate unstructured paragraph text. Depending on the data model, we found that a patient’s full cancer history can take up to 8 hours to curate. Therefore, we want to implement AI to automate the curation of this data to save time and cost. We hope to achieve a faster curation process that allows us to accomplish more than 1 patient a day to catch up to the 100,000 MSK-IMPACT cohort. To decrease the average curation time per patient, we investigated the use of an NLP model to replicate manual curation of the PRISSMM™ ontology field for change in cancer status from radiology reports. Manual curation of radiology reports is time intensive due to curators understanding their cancer status and the volume of scans patients undergo. Methods:A pre-trained Bidirectional Encoder Representations from Transformers (BERT) model is fine-tuned using training data using GPUs in IBM Cloud Pak for Data (CPD) platform. The hyperparameters were adjusted using accuracy and F1 metric of evaluation data. Using one vs. rest approach the model is evaluated on held out test data with results shown in table 1.Table 1 includes class 1-5: Progressing/worsening/enlarging, stable/no change, improving/responding, not stated/indeterminate or mixed. Summary:The weighted AUCROC ~ 0.97, F1 ~ 0.85 and accuracy ~ 93%. These metric scores improve by choosing notes with higher class probabilities only. Conclusion:Due to the above 0.9 calculated accuracy this NLP model is successful in replicating the curated results of cancer status and the next steps will be to run this model on a new cohort of patients not yet curated. Cancer Status Metrics Class Prevalence Precision Recall F1 Score AUCROC Accuracy 1 38.9% 88.7% 87.0% 87.9% 96.5% 90.7% 2 24.7% 89.9% 88.2% 89.1% 98.3% 94.6% 3 15.9% 87.6% 90.7% 89.1% 98.7% 96.5% 4 15.7% 77.0% 72.6% 74.7% 94.4% 92.3% 5 4.8% 68.1% 74.4% 71.1% 97.9% 97.1% Weighted Average 85% 86% 85% 97% 93% Citation Format: Ankur Arya, Andrew Niederhausern, Nadia S. Bahadur, Neil J. Shah, Chelsea Nichols, Avijit Chatterjee, John Philip. Detection of status of cancer in radiology notes using artificial intelligence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4965.
Abstract 6477: Modulators of hospital length of stay after intracranial neoplasm excision
Authors: Jayla Hsiung, Kamil Taneja, Lauren Ladehoff, Karan Patel, Eric Toloza
Journal: Cancer Research (2024)

Abstract Purpose: Intracranial neoplasms are the leading cause of cancer death among men under 40 years old. A major part of the standard of care is excision of the tumor, but there is a lack of robust large-patient studies of outcomes for these patients. Methods: The Nationwide Inpatient Sample was queried from 2018 to 2020 to identify patients with an intracranial neoplasm. Multivariable linear regression with patient- and hospital-level characteristics as covariates was used to identify factors associated with long hospital stays. Results: From 2018 to 2020, there were 97,795 hospital encounters with a primary diagnosis of an intracranial neoplasm. Of these patients, 64.6% underwent a tumor excision procedure during their hospital visit. The average age of these patients undergoing excision was 57.80.2 years. Most patients were male (58.6%), white (79.1%), private insurance beneficiaries (46.3%), and of the highest income quartile (26.8%). These patients most commonly presented to hospitals in the West (34.9%), with a medium number of beds (36.4%), and presented to rural hospitals (41.7%). The most common locations of these neoplasms were the frontal (29.1%), temporal (21.3%), and parietal (12.1%) lobes. Neoplasms in more than one location in the brain occurred in 4.5% of patients. Multivariable linear regression identified the following factors as significantly associated with longer hospital stays: identifying as Black (beta=2.08; p&amp;lt;0.001), identifying as an Asian or Pacific Islander (beta=1.22; p=0.017), being a Medicaid beneficiary (beta=2.25; p&amp;lt;0.001), and being uninsured (beta=1.63; p&amp;lt;0.001). Having a neoplasm in the cerebral ventricle (beta=4.93; p&amp;lt;0.001), cerebellum (beta=2.81; p&amp;lt;0.001), or brain stem (beta=3.45; p&amp;lt;0.001), and having multiple neoplasms (beta=1.85; p=0.008) were also associated with longer hospital stays. Interestingly, having a parietal (beta=-0.54; p=0.011) or occipital (b=-0.99; p&amp;lt;0.001) lobe neoplasm was associated with shorter hospital stays. Conclusion: Intracranial neoplasms are deadly condition and excision of tumor is a important life-saving treatment option. In this study, we demonstrated that location of neoplasm, race, and insurance status are significant modulators of the length of a hospital stay after surgery. Citation Format: Jayla Hsiung, Kamil Taneja, Lauren Ladehoff, Karan Patel, Eric Toloza. Modulators of hospital length of stay after intracranial neoplasm excision [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6477.