bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 4654: Targeting poly-resistant stem cells in high-grade serous ovarian cancer via synthetic lethal drugs
Authors: Xian Wa , McKeon Frank , Crum Christopher , Ajani Jaffer , Davies Peter , Vincent Matthew , Bachovchin William , Lai Hung-Sen , Pan Shuang , Khorrami Melina , khorrami Melika , Montes Raul caballero , Mosaffa Paria , Hoffman Ashley , Su Amber
Published: March 2024

High-grade serous ovarian cancer (HGSOC) is remarkably responsive to chemotherapy and yet recurs at high rates as resistant disease. Using novel technology that selects for rare clonogenic cells which recapitulate HGSOC in immunodeficient mice, we have identified, in therapy-naive HGSOC, a minor population of clones that are intrinsically resistant to paclitaxel/carboplatin as well as to a broad spectrum of oncology drugs. These intrinsic "polyresistant" cells are a common, albeit minor, component of clonogenic cells in all therapy-naive tumors analyzed. Importantly, the polyresistant clonogenic cells share a gene expression signature distinct from the majority of clonogenic cells that are exquisitely sensitive to paclitaxel/carboplatin, and this gene signature of polyresistant cells extends to all polyresistant clones within a patient and across HGSOC cases. We have exploited these polyresistant clones to perform high-throughput screening of small molecule "bioactive" libraries to identify compounds that circumvent this resistance. While single agent "hits" were obtained, these showed minimal therapeutic windows relative to normal stem cells of the liver and gastrointestinal tract. Adaptations of synthetic lethal strategies have yielded lead drug combinations that eliminate polyresistant clones from all four cases tested at low nanomolar concentrations in vitro. We have improved these combinations via the synthesis of new chemical entities that show potent effects against both subcutaneous and peritoneal tumor models in immunodeficient mice derived from polyresistant HGSOC clones. Clonogenic analyses of these treated and untreated xenografts support the notion that these drug combinations are targeting the stem cell populations within these tumors. We anticipate that these drug combinations will assist in preventing or treating recurrent HGSOC.

Citation Format: Wa Xian, Frank McKeon, Christopher Crum, Jaffer Ajani, Peter Davies, Matthew Vincent, William Bachovchin, Hung-Sen Lai, Shuang Pan, Melina Khorrami, Melika khorrami, Raul caballero Montes, Paria Mosaffa, Ashley Hoffman, Amber Su. Targeting poly-resistant stem cells in high-grade serous ovarian cancer via synthetic lethal drugs [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 4654.
Abstract 4676: 11α-O-2-methylbutanoyl-12β-O-tigloyl-tenacigenin B (MT2) is a novel paclitaxel chemosensitizer to inhibit growth in Taxol non-resistant and Taxol resistant cancers
Authors: Cheng Ka Ming , Wu Gui yun , Cheung Kowk Kuen , Shen Xiao-Ling , Hu Ying-Jie , Lui Ki
Published: March 2024

11α-O-2-methylbutanoyl-12β-O-tigloyl-tenacigenin B (MT2) is a single molecule isolated from a traditional Chinese Medicinal herb Marsdenia tenacissima (MT). Recently, our group has isolated a few single molecules from the MT herb, they have shown significant anti-tumor activity in vitro and MT2 has the highest potential among all. We have performed MTT viability assay and clonogenic assay to demonstrate that MT2-alone is non-cytotoxic, but the cytotoxicity of the paclitaxel+MT2 combination treatment was more significant than that of paclitaxel, a microtubule stabilizing chemotherapeutic agent. The underlying mechanism of such growth inhibition is contributed by the down-regulation of the pro-survival signaling and up-regulation of the apoptotic signaling such as an increase in cleaved caspase 3 and decrease in anti-apoptotic Bcl-2 proteins when cancer cells are co-treated with MT2+paclitaxel. More importantly, intraperitoneal administration of the combination treatment 5 times of MT2+paclitaxel (30mg/kg, 8mg/kg) has a more significant anti-tumor effect than the paclitaxel-alone (8mg/kg) or MT2-alone (30mg/kg) treatments using the wild-type hepatic HepG2 xenograft model in nude mice. Besides the wild-type HepG2 cancer cells, we have further demonstrated that MT2 is able to resensitize paclitaxel-resistant HepG2 cancer cells by inhibiting the activity of p-glycoprotein (Pgp), a key drug efflux transporter in chemotherapy resistance cancer cells. Also, the combination treatment has shown a significant anti-tumor effect in HepG2/DOX Pgp-overexpressed xenograft in nude mice. Taken together, MT2 is a novel chemosensitiser in combination use with paclitaxel to treat cancer. It enhances cancer apoptosis by suppressing the anti-apoptotic and survival signaling pathways in cancer cells.

Citation Format: Ka Ming Cheng, Gui yun Wu, Kowk Kuen Cheung, Xiao-Ling Shen, Ying-Jie Hu, Ki Lui. 11α-O-2-methylbutanoyl-12β-O-tigloyl-tenacigenin B (MT2) is a novel paclitaxel chemosensitizer to inhibit growth in Taxol non-resistant and Taxol resistant cancers [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 4676.
Abstract 4727: Large scale drug response comparison across different neuroblastoma cell model systems
Authors: Park Se Whee , Liu Ernest , Los Aironas , Seashore-Ludlow Brinton , Östling Päivi , Molenaar Jan , Kallioniemi Olli , Stenman Jakob , Karlsson Kasper
Published: March 2024

Traditionally neuroblastoma research has predominantly used 2D cell lines, which, despite their simplicity, often fall short in mirroring the physiological complexity of actual tumors. Recently, 3D models like patient-derived tumor organoids (PDO) and patient-derived xenografts (PDX) have emerged as superior alternatives, offering more realistic predictions of patient treatment responses. This study aims to discern the differences in drug response between conventional 2D cell lines and the more advanced 3D neuroblastoma models - specifically, patient-derived organoids (nPDO) and patient-derived xenograft organoids (nPDXO). Employing high-throughput drug screening of 528 cancer drugs, we evaluated the drug responses across traditional 2D cell lines, nPDOs, and nPDXOs. Additionally, focused experiments with 29 selected drugs were conducted to determine the influence of culture topology on drug efficacy. The findings were compared to a study by Hansson et al.1 that used nPDXO. Our study discovered a pronounced difference in drug sensitivity between 2D cell lines and 3D models, with 3D models showing heightened sensitivity. Interestingly, 2D cell cultures had a more heterogenous drug response compared to 3D models. The drug response correlation between nPDOs and nPDXOs was relatively high (Spearman ~0.8), indicating consistent responses across these models. Our comparison underscores the impact of model system choice on drug response studies in neuroblastoma. The study highlights important differences in drug response between neuroblastoma 2D and 3D cell culture models. However, only subtle differences were found between PDO and PDX-derived organoid lines, despite differences in treatment centers and media compositions. This suggests that while the choice of cell culture topology greatly impacts drug response, PDO and PDX derived lines can largely be used interchangeably for drug screening experiments.

References: 1. Hansson et al, ﻿Therapeutic targeting of KSP in preclinical models of ﻿high-risk neuroblastoma, Science Translational Medicine(2020)

Citation Format: Se Whee Park, Ernest Liu, Aironas Los, Brinton Seashore-Ludlow, Päivi Östling, Jan Molenaar, Olli Kallioniemi, Jakob Stenman, Kasper Karlsson. Large scale drug response comparison across different neuroblastoma cell model systems [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 4727.
Abstract 4738: Overcoming therapy resistance in rhabdomyosarcoma by targeting the PI3K-MAPK pathway
Authors: Wang Yadong , Chen Eleanor
Published: March 2024

Rhabdomyosarcoma (RMS) is a devastating pediatric cancer. There has not been any significant change in the treatment options for the last 4 decades, especially for relapsed or advanced disease. There is an urgent need to identify alternative treatment options to improve survival outcomes of RMS patients. RMS is comprised of two major subtypes as defined by the presence or absence of PAX3/PAX7-FOXO1 gene fusion. Fusion-negative RMS (FN RMS) is characterized by alterations in the RAS-PI3K-MAPK pathway in >90% of the cases. However, the role of the PI3K-MAPK pathway in therapy resistance and disease relapse remains poorly characterized. We have generated two FN-RMS lines, RD and SMS-CTR, with resistance to the standard-of-care chemotherapeutic agent, vincristine, through long-term culturing in incrementally increased concentrations of the drug. By RNA sequencing, vincristine-resistant RD and SMS-CTR cells demonstrated increased expression of genes in the RAS-PI3K-MAPK pathway compared to the parental lines. We hypothesize that increased activity of the PI3K-MAPK pathway contributes to therapy resistance in FN RMS. To test the hypothesis, we first showed that targeted disruption of PIK3CA by shRNA inhibited the cell growth of vincristine-resistant FN RMS cells. The same cells also showed increased sensitivity to the MEK inhibitor, trametinib, as well as the PIK3Cα inhibitor, alpelisib, compared to the parental cells. We then showed that zebrafish FN-RMS tumors treated with the combination of vincristine and alpelisib significantly inhibited tumor growth compared to the treatment with each agent alone. Through integrative analysis of RNA sequencing and ATAC-seq data, we identified MYOD1 and NFATC2 as among the top candidate upstream regulators. Targeted disruption of either MYOD1 or NFATC2 by CRISPR/Cas9 reduced cell growth of vincristine-resistant FN RMS cells and altered expression of the genes in the PI3K-MAPK pathway, implicating MYOD1 and NFATC2 in driving abnormal activity of this pathway. To assess the relevance of our findings in the clinical settings, we showed that selective components in the PI3K-MAPK pathways are up-regulated in 3 matched primary-recurrence/metastasis paraffinized tissue samples of human FN RMS by the NanoString GeoMx Digital Spatial Profiler (DSP) platform. Our findings indicate that targeting the PI3K-MAPK pathway is a promising targeted therapy option for overcoming therapy resistance in RMS.

Citation Format: Yadong Wang, Eleanor Chen. Overcoming therapy resistance in rhabdomyosarcoma by targeting the PI3K-MAPK pathway [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 4738.
Abstract 4793: Effects of treatment delays on lung cancer survival
Authors: Montero Percy Guzman , Cordero Sharon Segura
Published: March 2024

Background: Previous studies have established a link between treatment initiation delays and reduced overall survival in individuals diagnosed with lung cancer. These delays are often influenced by diagnostic complexities, logistical hurdles, and patient-related factors. However, the association between treatment delays and survival outcomes has yet to be extensively investigated using data from a large national cohort. This study aims to fill this research gap and provide unique insights into the relationship between treatment delays and lung cancer survival by utilizing data from a substantial national cohort.

Methods: The study population consisted of 3,723 lung cancer patients participating in the NCI PLCO Cancer Screening Trial. Cox Proportional Hazards (PH) Regression analyses examined the time between cancer diagnosis and treatment initiation using several measures including intervals from tumor doubling/stage progression time models by Spratt et al. (1964) and Detterbeck et al. (2008). Analyses controlled for patient and clinical characteristics including age, sex, race/ethnicity, smoking status, histopathologic type, cancer stage, and treatment modality. Data analysis was conducted using Microsoft Excel, STATA, and IBM SPSS software.

Results: PH Regression analyses demonstrated a clear association between longer time intervals from diagnosis to treatment initiation and increased risk of mortality. Patients with time intervals exceeding 20 days exhibited a hazard ratio (HR) for mortality of 1.21 (p < 0.001, 95% confidence interval [CI] 1.1158-1.3176). The Spratt tumor progression model, considering intervals exceeding 88 days, revealed a HR of 1.22 (p = 0.03, 95% CI 1.0146-1.4885). On the other hand, the Detterbeck model, which considered intervals exceeding 118 days, did not show a statistically significant association with increased mortality risk. Furthermore, PH analysis identified cigarette smoking status, marital status, and tumor grade as significant predictors of mortality risk.

Conclusions: Data from a large national cohort study indicate that delays in lung cancer treatment initiation have detrimental impacts on survival. Treatment initiation shortly after diagnosis had the most significant differential impact on mortality risk. Timely initiation of treatment is of utmost importance and should be prioritized in lung cancer care. By addressing factors contributing to treatment delays, it is likely possible to improve the survival rates of patients with lung cancer.

Citation Format: Percy Guzman Montero, Sharon Segura Cordero. Effects of treatment delays on lung cancer survival [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 4793.
Abstract 4854: Breast cancer incidence trends in Ukraine 2010-2019: Rising incidence at young ages
Authors: Verovkina Nataliia , Sumkina Olena , Syvak Liubov , El-Diery Wafik
Published: March 2024

Background. BC commonly affects women of older age, however, in developing countries around 20-25% cases of BC presented in young woman. Age-specific clinical characteristics or outcomes data for young women are lacking. Most of the standard treatments used in this subpopulation currently are derived from older patients. Early onset BC is often defined aggressive in nature. Several research have attributed this to a hidden unique biology. However, findings remain controversial.

Purpose: The aim of this study is to describe recent trends for BC incidence in Ukraine since 2010 by age groups and interpret them to seek clue for improvement.

Methods: We analyzed records from the NCR on 143420 BC cases (C50, International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10)) diagnosed in 2010-2019 in female Ukrainian population. The data were submitted on the beginning of 2022. We calculated annual age-standardized incidence rates (ASRWs) for three age groups. The estimated annual percent change (EAPC) of the rates was calculated using the generalized linear regression. The difference of the rates with its statistical significance was determined with the standardized rate ratio.

Results: During 2010-2019, the proportion of BC in all cancers detected at the age of 20-44 increased from 21.7% to 25.9%, while the frequency of BC detection at the age of 45+ did not change and ranged 19.3-20.2%. During the study period, the BC incidence rate has increased significantly (≤0.01): the ASRW of females aged 0-85+ grew with EAPC=0.6% amounting to 42.4-45.7 per 100,000 population, the incidence rate of women aged 45+ grew with EAPC=0.3% ranging from 130.0 to 139.6 per 100,000 population, while the incidence rate of women aged 20-44 grew with EAPC=1.8% amounting to 22.8-27.8 per 100,000 population. In age group 20-44 years, EAPC of BC incidence (1.8%) significantly exceeds the EAPC of the incidence for all cancers combined (0.2%). The dynamics of stage distribution showed increasing proportion of BC cases detected in women aged 20-44 in stage 1 (by 4.1% from 2010 to 2019) and its decreasing for BC cases detected in stage 2 by 4.5%; the proportion of cases diagnosed in stage 4 decreased by 0.5% along with increase in number of cases with undefined stage by 0.6%.

Conclusions: The obtained results indicate trends for increasing the incidence of Early Onset BC in Ukraine and justify need for the further research elucidating prognosis and validating novel biomarkers for customizing therapy for this patient group .

Citation Format: Nataliia Verovkina, Olena Sumkina, Liubov Syvak, Wafik El-Diery. Breast cancer incidence trends in Ukraine 2010-2019: Rising incidence at young ages [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 4854.
Abstract 4859: Mental health of early-onset and late-onset cancer survivors
Authors: Lee Jayden H. , An Jaejin
Published: March 2024

Background: Psychiatric disorders such as anxiety and depression are shown to be common when diagnosed with early-onset cancer, often defined as cancers diagnosed in adults <50 years of age. We hypothesize that the mental health of early-onset cancer survivors is negatively affected compared to late-onset cancer survivors.

Methods: We identified cancer survivors in the Medical Expenditure Panel Survey 2021 Full Year Consolidated Data File. We categorized cancer survivors as early-onset (≤ 50 years of age) and late-onset (> 50 years of age). We examined the proportion of mood and anxiety disorders, and the proportion of antidepressant and antianxiety medication use among the early and late-onset cancer survivors. We conducted chi-square tests and multivariable logistic regression models by adjusting for sex and race.

Results: We identified 291 early-onset cancer survivors (mean age 41 years, 71% female) and 2556 late-onset cancer survivors (mean age 71 years, 56% female). Among the early-onset cancer survivors, 18% had mood disorders (17% took antidepressants) and 20% had anxiety disorders (6% took antianxiety medication). In comparison, 12% late-onset cancer survivors had mood disorders (21% took antidepressants) and 13% had anxiety disorders (8% took antianxiety medication). Early-onset cancer survivors were more likely to develop mood (Adjusted Odds Ratio (aOR)=1.45; 95% CI=1.06 - 1.99) and anxiety (aOR=1.42; 95% CI=1.05 - 1.92) disorders compared to late-onset cancer survivors. However, there were no differences in receiving antidepressants (aOR=0.79; 95% CI=0.57 - 1.09) or antianxiety (aOR=0.69; 95% CI=0.41 - 1.16) medication between early and late-onset cancer survivors when adjusting for sex and race.

Conclusion: Early-onset cancer survivors had an elevated risk of acquiring psychiatric disorders such as mood and anxiety disorders than late-onset cancer survivors, but treatment was suboptimal. Clinician and patient awareness can help narrow the gaps of treatment for early-onset cancer survivors.

Table 3. Odds Ratio for early-onset vs. late-onset cancer survivors (*Sex and Race adjusted) Variables Crude Odds Ratio Adjusted Odds Ratio * Mood Disorders 1.48 (1.09 - 2.00) 1.45 (1.06 - 1.99) Anxiety Disorder 1.52 (1.13 - 2.03) 1.42 (1.05 - 1.92) Antidepressants 0.80 (0.59 - 1.10) 0.79 (0.57 - 1.09) Antianxiety 0.70 (0.42 - 1.17) 0.69 (0.41 - 1.16)

Citation Format: Jayden H. Lee, Jaejin An. Mental health of early-onset and late-onset cancer survivors [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 4859.
Abstract 4860: Recommendations for enhancing inclusion and management of esophagus cancer clinical trials: Insights on mortality of esophagus cancer as a second primary malignancy
Authors: Zhou Haiyu , Leng Jinhang , Qiu Hongrui , Huang Qizhi , Zhang Jinqiang
Published: March 2024

Background: Esophagus cancer as a second primary malignancy (esophagus-2) is increasingly common, but its prognosis is poorly understood. This study aims to examine the overall, non-cancer related and cancer-specific survival of patients diagnosed with esophagus-2 compared to the first primary esophagus cancer (esophagus-1).

Methods: We included primary esophagus cancer patients diagnosed from 1975 to 2020 in the Surveillance, Epidemiology, and End Results program. Esophagus-2 was identified in patients with a previous diagnosis of non-esophageal primary malignancy. Hazard ratios of overall, esophagus cancer-specific and non-cancer related mortality were estimated among patients with esophagus-2 compared to esophagus-1, adjusting for age, sex, tumor stage and other demographic and clinical characteristics.

Results: A total of 74521 and 14820 patients were identified as esophagus-1 and esophagus-2. Esophagus-2 patients suffered lower risk of esophagus cancer-specific mortality in initial 5 years but similar risk thereafter, independent of tumor characteristics and treatment. In the first 5 years after diagnosis, patients with esophagus-2 had similar risk of overall mortality with those with esophagus-1 but increased risk thereafter. As for non-cancer related mortality, esophagus-2 patients had higher risk all along.

Conclusion: Patients diagnosed with esophagus-2 face a favorable esophagus cancer-specific survival within the early period after diagnosis. However, patients with esophagus-2 are more liable to die of non-cancer cause. A conservative approach to manage esophagus-2 solely based on malignancy history is not supported but effort should be put into surveillance, prevention and management of the comorbidities and complications for the first malignancy.

Citation Format: Haiyu Zhou, Jinhang Leng, Hongrui Qiu, Qizhi Huang, Jinqiang Zhang. Recommendations for enhancing inclusion and management of esophagus cancer clinical trials: Insights on mortality of esophagus cancer as a second primary malignancy [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 4860.
Abstract 4887: Unveiling the functional impact of glioma non-coding germline variants using large language models
Authors: Alvarez-Torres Maria del Mar , Fu Xi , Sagatelian Romella K , Buendia Alejandro L , Rabadan Raul
Published: March 2024

Efforts to identify the risk for developing gliomas through Genome-Wide Association Studies (GWAS) face relevant challenges, such as accurately pinpointing the genomic positions of germline variants, primarily found in non-coding regions, with unclear functional implications in glioma development. In this context, the GET method, a large language model designed to unveil regulatory grammars across 213 human cell types, emerges as a valuable tool for elucidating the mechanisms of non-coding mutations.

Our aims include: I) Validate the efficacy of the GET method using a well-documented case and prioritize relevant variants for analysis; II) Refine the genomic positions of these variants and exploring their linkage disequilibrium (LD); III) Identify potential motifs and genes that might be influenced by these high-impact variants.

After examining published GWAS, 39 non-coding SNPs in gliomas were found. Adding 316 variants in high LD (R2 > 0.8) expanded the dataset to 355 variants for analysis. Using the GET method, we calculated impact scores (ISs) for each variant, considering changes in motif binding score (ΔBM) and motif gradient (GM) across human astrocytes. We focused on rare variants (risk allele frequency <0.25) with the higher odds ratios (OR).

The table presents GET results for a well-known case-control, showing its role in increasing glioma risk through OCT4 motif disruption and enhanced MYC expression, as previously was confirmed experimentally. Moreover, it details results concerning the 5 rare germline variants exhibiting the highest ISs, including precise genomic positions and the most affected motifs and genes that could potentially be impacted by each variant.

Using a large language model, this study overcomes the challenge of mere variant identification, aiming to establish a framework for uncovering the underlying mechanism of risk variants. While further validation is essential, this is a promising approach to explore the impact of germline mutations.

Variant ID Genomic Position Altered Motif Affected Gene Ref allele Alt allele Case-control rs55705857 Chr8:129633445 OCT4+SOX2:POU MYC A G H-I variant #1 rs78378222 Chr17:7668433 HD/18 PER1 T G H-I variant #2 rs518394 Chr9:22019673 KLF/SP/2 CDKN2A G C H-I variant #3 rs79495512 Chr15:76199995 KLF/SP/2 LINGO1 T C H-I variant #4 rs78185702 Chr15:76317893 SMAD LINGO1 C T H-I variant #5 rs2538067 Chr7:54907724 CTCF EGFR G A

Citation Format: Maria del Mar Alvarez-Torres, Xi Fu, Romella K Sagatelian, Alejandro L Buendia, Raul Rabadan. Unveiling the functional impact of glioma non-coding germline variants using large language models [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 4887.
Abstract 489: Unlocking immune resistance and metastasis of PDAC via dual acting circularized nanodisc
Authors: Elzoghby Ahmed , Emam Hagar , Yim Seungbin , Xin Cuiyan , Nasr Mahmoud
Published: March 2024

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and deadliest forms of cancer. While major progress in immunotherapy has been made in recent years, it remains poorly effective in this malignancy. Two key players stand behind immune resistance of PDAC and inadequate efficacy of immunotherapy to suppress its metastasis. First, the immune-resistant pancreatic cancer stem cells (CSCs) evade immune surveillance acting as a source for tumor relapse and metastasis. This immune resistance stems from low immunogenicity of PDAC cells as well as the inaccessible CSCs that reside deep in the tumor core. Second, pancreatic cancer associated fibroblasts (CAFs) fuel metastasis of PDAC cells by suppressing their immune recognition and establishing pre-metastatic niche at distant organs to help their colonization. Our hypothesis is to overcome immune resistance of PDAC and inhibit early steps of its metastasis via simultaneous immunogenic eradication of immune resistant CSCs and switching immunosuppressive and pro-metastatic CAFs into quiescent ones. Therefore, we engineered ultrasmall circularized nanodiscs (cND) that encapsulate oncolytic peptide LTX-315 and fibroblast remodeling Notch signaling inhibitor. The engineered oncolytic LTX-315 loaded cND successfully induced immunogenic cell death (ICD) of both bulk PANC1 and pancreatic CSCs. Compared to non-treated and free LTX-315 treated cells, LTX-315 cND resulted in enhanced release of DAMPs including ATP and HMGB-1 as well as surface translocation of calreticulin. The ultrasmall size (9 nm) of cND enabled its deep tumor penetration to eradicate resistant CSCs, as revealed using 3D PDAC heterospheroids. In parallel, the Notch blocking cND promoted quiescence of the activated pancreatic stellate cells as denoted by downregulation of SMA, FAP and collagen. In KPC syngeneic PDAC mouse model, the dual oncolytic/Notch blocking cND combined with aPD-L1 therapy significantly suppressed tumor growth and prevented its metastasis to liver compared to vehicle-treated mice. Immunophenotyping study showed marked reduction in the abundance of CSCs and CAFs in the tumor treated with the cNDs. Moreover, the tumor infiltration of CD86+ MHCII+ dendritic cells and cytotoxic CD8+ T cells was enhanced after treatment with the cND. Overall, our dual strategy of targeting pancreatic CSCs and CAFs via oncolytic/Notch blocking cND boosted the anti-tumor and anti-metastatic efficacy of aPD-L1 therapy to eliminate primary PDAC tumor and suppress its metastasis.

Citation Format: Ahmed Elzoghby, Hagar Emam, Seungbin Yim, Cuiyan Xin, Mahmoud Nasr. Unlocking immune resistance and metastasis of PDAC via dual acting circularized nanodisc [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 489.
Abstract 4908: Comprehensive tool for pan-cancer consensus data mining of drugs, targets and biomarkers
Authors: Yoon Sukjoon
Published: March 2024

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the discovery of drug targets and biomarkers. For this purpose, we have developed a convenient tool, Q-omics software, for general researchers and cancer scientists to carry out customized data mining without bioinformatics background. Q-omics provides a comprehensive interface and smart functions for facilitating pan cancer-wide association studies on mutations, RNA expression, protein abundance, shRNA/CRISPR efficacy, drugs, tumor-infiltrating cells, patient survival, clinical info. etc. Furthermore, consensus scores on associated data pairs from heterogeneous samples, help to predict the reproducibility of data mining results. Q-omics (download: http://qomics.io) improves the utility of cancer omics big data for non-computational scientists at all levels of cancer research.

Citation Format: Sukjoon Yoon. Comprehensive tool for pan-cancer consensus data mining of drugs, targets and biomarkers [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 4908.
Abstract 4950: Applying fragmentomics profiles of plasma cell-free DNA for breast cancer detection
Authors: Liu Yaxin , Gan Shuang , Dong Hang , Tang Haoran , Wang Nan , Gui Xinyu , Zhu Anjie , Zhang Ruyan , Du Pan , Jia Shidong
Published: March 2024

The liquid biopsy approach focusing on DNA molecules supports the non-invasive diagnosis of breast cancer. Low-pass whole genome sequencing(lpWGS) for breast cancer detection has been validated for accuracy and cost-effectiveness, especially with copy number variant (CNV) analysis. However, detecting breast cancer with cell-free DNA (cfDNA) CNV was limited by tumor fraction. Utilizing cell-free DNA fragmentation characteristics for cancer detection has shown potential in plasma with high precision and applicability with low tumor fraction. In this study, 217 patients with breast cancer and 10 healthy individuals were enrolled. The cfDNA was extracted and performed using PredicineSCORE, a low-coverage whole genome sequencing assay to identify tumor-specific features. The cfDNA fragmentomics profiles including the coverage at specific regions, length and end-motif of fragment were implemented. We also investigated the copy number variation and the inferred tumor fraction which was adjusted by the Expectation-Maximum (EM) algorithm. Combining, an ensembled machine learning model was constructed for the classification of breast cancer and normal control. We observed a high correlation between tumor fraction and features. The absolute correlation coefficient scores between tumor fraction with the LYL1, MAF, FOXA1, and GRHL2 bonding sites' relative depth were over 0.82, 0.71,0.89,0.87. The insert size ratio of short reads and the CCCA end motif were over 0.77 and 0.72, respectively. We then diluted the tumor samples of tumor fraction at 0.1% to 50% by manually mixing reads from tumor samples into normal samples. By applying the XGBoost algorithm, the performance (F1 score > 0.95) showed a promising ability to distinguish tumors from normal samples. The limit of detection (LOD) was less than 1% which is more sensitive than previously proposed models. Those samples detected mutations with high through panel which can confirm the accuracy of the assay. Our results discovered that profiling the cell-free DNA fragment could facilitate the way of non-invasively detection of breast cancer with high precisions.

Citation Format: Yaxin Liu, Shuang Gan, Hang Dong, Haoran Tang, Nan Wang, Xinyu Gui, Anjie Zhu, Ruyan Zhang, Pan Du, Shidong Jia. Applying fragmentomics profiles of plasma cell-free DNA for breast cancer detection [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 4950.
Abstract 4953: A proposal to extend standardized organ mapping antibody panels (OMAPs) to integrate protein and RNA analysis in spatial biology
Authors: Müller Werner , Femel Julia , Neil Emily , Park Dongju , Hennessey Rebecca C. , DiBiasio Eric C. , DiBuono Michael , Lafayette Hanna , Lloyd Erica , Lo Hsinyi , Makrigiorgos Alex , Soliman Sameh , Mangiardi Dominic , Praveen Paurush , Rüberg Silvia , Staubach Fabian , Hindman Ryan , Rothmann Thomas , Meyer Hansueli , Wantenaar Tanya , Wang Jinling , Pinard Robert , Bosio Andreas
Published: March 2024

The HubMap consortium has developed a new standard to report on normal histological samples using multicolor immunofluorescence imaging. An Organ Mapping Antibody Panel (OMAP) currently describes in a table the antibodies used, the cycle number assigned to a given reagent, and provides the rationale for using a particular antibody to better understand features of the tissue. This table is accompanied by antibody validation templates that show example images from the tissue described for the OMAP table. In addition, links to existing databases, gene symbols, the antibody features and colors are included. For each tissue, a further table called "Anatomical Structures, Cell Types, plus Biomarkers" (ASCT+B), which contains structures of the tissue, cell types in a given tissue structure, key RNA transcripts for a given cell type, and antibody stains as used in the OMAP table, is created. So far, this process has not been established for spatial multiomic datasets including protein and RNA detected on the same tissue section.

We have extended spatial biology methodology to combine cyclic RNA transcript detection with cyclic antibody-based protein detection using the MACSima Imaging Cyclic Staining (MICS) technology as well as H&E-staining on the same tissue section. For such datasets, the current OMAP data table needs to be extended by adding information on the RNA detection, cycle IDs and RNA validation templates, demonstrating the correct performance of a given RNA probe detection.

This poster will demonstrate a proposal to extend the OMAP table structure on an extended version of the “tonsil OMAP (OMAP-10)”, which was published on the Zenodo data repository page (https://zenodo.org/records/7875938). In addition, we will apply this extended OMAP to a colorectal cancer sample, to highlight the applicability and relevance of the OMAP structure for tumor tissue.

Citation Format: Werner Müller, Julia Femel, Emily Neil, Dongju Park, Rebecca C. Hennessey, Eric C. DiBiasio, Michael DiBuono, Hanna Lafayette, Erica Lloyd, Hsinyi Lo, Alex Makrigiorgos, Sameh Soliman, Dominic Mangiardi, Paurush Praveen, Silvia Rüberg, Fabian Staubach, Ryan Hindman, Thomas Rothmann, Hansueli Meyer, Tanya Wantenaar, Jinling Wang, Robert Pinard, Andreas Bosio. A proposal to extend standardized organ mapping antibody panels (OMAPs) to integrate protein and RNA analysis in spatial biology [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 4953.
Abstract 4971: Integrating artificial intelligence and functional precision oncology for individualized cancer therapies
Authors: Eguiarte-Solomon Fernando , Prendergast Rowan , Carapia Bianca , Rodriguez Javier , Buck Kristen , Gorospe Derrick , Valencia Elizabeth , Lopez-Ramos Jose , Gutierrez Itzel , Pippa Rafaella , Chien Yuan-Hung , Andrews Warren , Do Long , Sperry Jantzen , Nakashima Jonathan K.
Published: March 2024

Precision oncology seeks to tailor cancer treatments to individual patients. Patient-derived xenografts (PDXs) have emerged as a promising platform for selecting efficacious, personalized therapies and developing new oncology drugs. Here, we present a workflow for selecting and validating treatments for patients with colorectal cancer (CRC) that integrates orthotopic PDX (O-PDX) models, molecular profiling, machine learning, and in vivo pharmacological validation. Of the nine tumor biopsies collected, seven were successfully developed into O-PDX models (78%) with a median time to establishment of 119 days. Models were molecularly profiled for gene expression and were serially passaged to perform orthotopic pharmacology studies to validate test agents selected by oncologists as well those suggested by CertisAITM, a novel ensemble of machine learning models for the prediction of drug response in human cancers. The correlation between CertisAI's predicted therapy responses and the actual observed tumor growth inhibition (TGI) was r = 0.7, encompassing 37 distinct treatments across studies from six patients. This research collectively illustrates that the integration of artificial intelligence with functional in vivo assays offers a powerful platform for precision oncology, enabling the identification and validation of tailored treatments for individual cancer patients.

Citation Format: Fernando Eguiarte-Solomon, Rowan Prendergast, Bianca Carapia, Javier Rodriguez, Kristen Buck, Derrick Gorospe, Elizabeth Valencia, Jose Lopez-Ramos, Itzel Gutierrez, Rafaella Pippa, Yuan-Hung Chien, Warren Andrews, Long Do, Jantzen Sperry, Jonathan K. Nakashima. Integrating artificial intelligence and functional precision oncology for individualized cancer therapies [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 4971.
Abstract 4974: Development of an ovarian cancer diagnosis score using electronic health records
Authors: Phung Minh Tung , McLean Karen , Hanley Gillian E. , Pearce Celeste Leigh
Published: March 2024

Background: Diagnosis of invasive epithelial ovarian, fallopian tube, and primary peritoneal cancers (hereafter referred to as ovarian cancer) is often delayed, worsening both survival and quality of life for ovarian cancer patients. Diagnosis is delayed in ovarian cancer both because there is no effective screening method and because the symptoms commonly associated with ovarian cancer (i.e., abdominal/pelvic pain, bloating, loss of appetite, urinary symptoms) are non-specific to the disease. It would be beneficial to develop a flag in the electronic health record (EHR) when a patient’s healthcare utilization indicates further investigation for possible ovarian cancer is warranted. Thus, we used EHR data to develop a diagnosis score that identifies people who should be further assessed for potential ovarian cancer.

Methods: EHR data from 211,123 female patients, including 135 ovarian cancer patients, at the University of Michigan Medical System during 2012-2023 were analyzed. Time-varying Cox proportional hazard models were fit to identify the association between ovarian cancer and the diagnostic codes recorded for healthcare visits in the EHR, including the temporal sequence of the diagnostic codes. The beta coefficients for the diagnosis codes from the Cox models were summed to create a weighted diagnosis score for each patient. The weighted diagnosis score was tested for association with ovarian cancer in the same population.

Results: A total of 79 diagnostic codes were statistically significantly associated with ovarian cancer after applying a Bonferroni correction (p<9x10-5). The temporal sequence of the diagnoses was not associated with ovarian cancer. There were 11 pairs of diagnosis codes that were correlated (correlation coefficient >0.25); the diagnosis code with the higher p-value was excluded from further consideration. The remaining 68 codes were used to construct the diagnosis score. There was a statistically significant trend of increasing rate of ovarian cancer per quartile of the diagnosis score (hazard ratio=3.75, 95% confidence interval 3.50-4.03).

Conclusion: A score for ovarian cancer diagnosis was developed based on 68 diagnostic codes in the EHR. The next step is to validate the diagnosis score in an external dataset. This validation is underway using administrative data from British Columbia, Canada.

Citation Format: Minh Tung Phung, Karen McLean, Gillian E. Hanley, Celeste Leigh Pearce. Development of an ovarian cancer diagnosis score using electronic health records [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 4974.
Abstract 4976: The impact of obesity on survival in epithelial gynecological tumors
Authors: Badran Ahmed , Elshenawy Mahmoud , Fallatah Waleed , Hinkston Abdullaah K. , Ali Saad S. , Omar Mohammed Ali , Alaklabi Abdulaziz M. , Abdalla Hytham M. , Arabi Tarek Z. , Sabbah Belal N. , Alhusaini Hamed
Published: March 2024

Background: The impact of obesity on the survival of patients with epithelial gynecological tumors is not yet clear. We aim to elucidate the impact of body mass index (BMI) on epithelial gynecological tumors in a large tertiary center at Saudi Arabia.

Methods: We retrospectively reviewed the medical files of all patients with pathologically confirmed epithelial gynecological tumors at our center. Then, we assessed the difference in overall survival (OS) according to primary tumor location, BMI, stage at presentation, and performance status (PS) at presentation using log-rank tests.

Results: 400 patients were included in the analysis. The mean age at diagnosis was 56.1±13 years. 242 (60.5%) patients were diagnosed with uterine carcinomas, 137 (34.3%) with ovarian carcinomas, and 21 (5.3%) with cervical carcinomas. 278 (69.5%) patients were obese at presentation, 74 (18.5%) were overweight, 43 (10.8%) were within normal range, and 7 (1.8%) were underweight. The PS at presentation was 0, 1, 2, 3, and 4 in 351 (87.8%), 17 (4.3%), 10 (2.5%), 16 (4%), and 6 (1.5%) patients, respectively. Cervical cancer was associated with long OS, while ovarian cancers demonstrated poor prognosis (p=0.0159). There was no difference in OS between different BMI groups (p=0.072). Patients with stage 4 cancers had significantly shorter OS (p<0.0001). Patients with PS 4 at presentation was associated with the worst prognosis (p<0.0001).

Interpretation: Shorter OS was associated with ovarian carcinomas, advanced staging, and poor PS at presentation. BMI classification had no impact on OS. Further studies are needed to confirm our findings.

Citation Format: Ahmed Badran, Mahmoud Elshenawy, Waleed Fallatah, Abdullaah K. Hinkston, Saad S. Ali, Mohammed Ali Omar, Abdulaziz M. Alaklabi, Hytham M. Abdalla, Tarek Z. Arabi, Belal N. Sabbah, Hamed Alhusaini. The impact of obesity on survival in epithelial gynecological tumors [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 4976.
Abstract 4997: Auranofin enhances the efficacy of anti-PD1 immunotherapy
Authors: Zhao Zichen , Hu Shichuan , Zhang Yan
Published: March 2024

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.