Tumor Histopathology Research Articles

The effect of 11th rib excision on perioperative outcomes in patients undergoing partial nephrectomy for upper pole renal tumors

IntroductionWe aimed to evaluate the effect of eleven11th rib resection.on the perioperative period TRIFECTA criteria in patients who underwent retroperitoneal partial nephrectomy (PN) with the diagnosis of upper pole kidney tumors.Materials and methodsWe conducted a retrospective analysis of the data of the patients who underwent Open PN for upper pole renal masses between 2018 and 2023. The patients were divided into two groups: PN with rib resection and PN without rib resection. The demographic characteristics, tumor sizes, PADUA scores, warm–cold renal ischemia times, mass excision and tumor bed suturing times, histopathological tumor type and surgical margin positivity of the patients were examined. Both groups were evaluated comparatively based on this data.ResultsThe renal nephrometry scores of the two groups were similar. The total renal ischemia time was significantly shorter in the patients who underwent a rib resection than in those who did not (p < 0.001). Both the tumor excision and tumor bed suturing times were significantly shorter in the group that underwent a rib resection than in the group that did not (p < 0.001). The Clavien–Dindo complication grades were statistically similar between the two groups.ConclusionComplex in nature and high–risk renal masses located in the upper pole of the kidney, partial nephrectomy performed with an 11th rib resection can be considered a reliable surgical option with a shorter ischemia time, supporting the preservation of long-term renal function.

Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning.

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven means to enhance diagnostic accuracy but are also time consuming and not widely available. Here, to address these limitations, we developed Deep lEarning from histoPathoLOgy and methYlation (DEPLOY), a deep learning model that classifies CNS tumors to ten major categories from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from slide images ('direct model'), the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification ('indirect model'), and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicts beta values from histopathology images. Second, using a ten-class model trained on an internal dataset of 1,796 patients, we predict the tumor categories in three independent external test datasets including 2,156 patients, achieving an overall accuracy of 95% and balanced accuracy of 91% on samples that are predicted with high confidence. These results showcase the potential future use of DEPLOY to assist pathologists in diagnosing CNS tumors within a clinically relevant short time frame.

Leveraging radiomics and AI for precision diagnosis and prognostication of liver malignancies.

Liver tumors, whether primary or metastatic, have emerged as a growing concern with substantial global health implications. Timely identification and characterization of liver tumors are pivotal factors in order to provide optimum treatment. Imaging is a crucial part of the detection of liver tumors; however, conventional imaging has shortcomings in the proper characterization of these tumors which leads to the need for tissue biopsy. Artificial intelligence (AI) and radiomics have recently emerged as investigational opportunities with the potential to enhance the detection and characterization of liver lesions. These advancements offer opportunities for better diagnostic accuracy, prognostication, and thereby improving patient care. In particular, these techniques have the potential to predict the histopathology, genotype, and immunophenotype of tumors based on imaging data, hence providing guidance for personalized treatment of such tumors. In this review, we outline the progression and potential of AI in the field of liver oncology imaging, specifically emphasizing manual radiomic techniques and deep learning-based representations. We discuss how these tools can aid in clinical decision-making challenges. These challenges encompass a broad range of tasks, from prognosticating patient outcomes, differentiating benign treatment-related factors and actual disease progression, recognizing uncommon response patterns, and even predicting the genetic and molecular characteristics of the tumors. Lastly, we discuss the pitfalls, technical limitations and future direction of these AI-based techniques.

Sensitivity of magnetic resonance elastography to extracellular matrix and cell motility in human prostate cancer cell line-derived xenograft models

Prostate cancer (PCa) is a significant health problem in the male population of the Western world. Magnetic resonance elastography (MRE), an emerging medical imaging technique sensitive to mechanical properties of biological tissues, detects PCa based on abnormally high stiffness and viscosity values. Yet, the origin of these changes in tissue properties and how they correlate with histopathological markers and tumor aggressiveness are largely unknown, hindering the use of tumor biomechanical properties for establishing a noninvasive PCa staging system.To infer the contributions of extracellular matrix (ECM) components and cell motility, we investigated fresh tissue specimens from two PCa xenograft mouse models, PC3 and LNCaP, using magnetic resonance elastography (MRE), diffusion-weighted imaging (DWI), quantitative histology, and nuclear shape analysis. Increased tumor stiffness and impaired water diffusion were observed to be associated with collagen and elastin accumulation and decreased cell motility. Overall, LNCaP, while more representative of clinical PCa than PC3, accumulated fewer ECM components, induced less restriction of water diffusion, and exhibited increased cell motility, resulting in overall softer and less viscous properties. Taken together, our results suggest that prostate tumor stiffness increases with ECM accumulation and cell adhesion - characteristics that influence critical biological processes of cancer development.MRE paired with DWI provides a powerful set of imaging markers that can potentially predict prostate tumor development from benign masses to aggressive malignancies in patients. Statement of significanceXenograft models of human prostate tumor cell lines, allowing correlation of microstructure-sensitive biophysical imaging parameters with quantitative histological methods, can be investigated to identify hallmarks of cancer.

Complex treatment of residual metastatic germ cell cancer: A single center experience

BackgroundTesticular cancer is the most common solid malignancy among men aged 15–35. Radical orchiectomy and platinum-based chemotherapy (BEP) are curative in the majority of patients, including advanced, metastatic cases. According to current urooncology guidelines all non-seminoma patients harbouring post-chemotherapy residual masses of ≥ 1 cm should undergo salvage retroperitoneal lymph node dissection (RPLND). However, only 10% of residual tumors contain viable disease. ObjectiveTo assess patient outcomes and complications considering different treatment regimens and clinical characteristics. Materials and methodsIn a retrospective cross-sectional study patients (n=127) who underwent postchemotherapy RPLND between 2007 and 2023 at our referral center were evaluated. The patients received systemic treatment at various oncology centers. The number of BEP cycles received were occasionally different from standard. Only patients with normal postchemotherapy serum tumor markers and primary testicular or extragonadal germ cell neoplasms were included. Treatment groups were established according to the number of BEP cycles received, and the extent of RPLND (bilateral or modified template). Treatment outcomes and complications were assessed. ResultsStandard 3–4 courses of BEP were received by 100 (78,7%) patients, while 11 (8,7%) patients underwent less, and 16 (12,6%) more courses than standard. On histopathologic evaluation viable germ cell tumor, teratoma, and necrosis/fibrosis was present in 26 (20,5%), 67 (52,7%) and 34 (26,8%) of specimen, respectively. In the 5–6 BEP series subgroup high rate of viable disease (37,5%) was found and significantly more nephrectomies were performed, than other chemotherapy subgroups. Extratesticular GCT, viable disease in residual mass or progression after RPLND indicated lower survival. Mild (Clavien-Dindo I-II) or no postoperative complications were reported in 93,7% of cases. ConclusionsThe study suggests no significant benefit from exceeding 3–4 courses of BEP. Timely salvage RPLND should be performed in high volume centers for optimal treatment outcomes with acceptable complication rates. Adherence to the Heidenreich criteria is advisable where practical.

A case of pulmonary melioidosis in Germany: a rare differential diagnosis in returning travelers from South-East Asia

BackgroundMelioidosis is a bacterial infection associated with high mortality. The diagnostic approach to this rare disease in Europe is challenging, especially because pulmonary manifestation of melioidosis can mimic pulmonary tuberculosis (TB). Antibiotic therapy of melioidosis consists of an initial intensive phase of 2–8 weeks followed by an eradication therapy of 3–6 months.Case presentationWe present the case of a 46-year-old female patient with pulmonary melioidosis in Germany. The patient showed chronic cough, a pulmonary mass and a cavitary lesion, which led to the initial suspicion of pulmonary TB. Melioidosis was considered due to a long-term stay in Thailand with recurrent exposure to rice fields.ResultsMicrobiologic results were negative for TB. Histopathology of an endobronchial tumor showed marked chronic granulation tissue and fibrinous inflammation. Melioidosis was diagnosed via polymerase chain reaction by detection of Burkholderia pseudomallei/mallei target from mediastinal lymph-node tissue.ConclusionThis case report emphasizes that melioidosis is an important differential diagnosis in patients with suspected pulmonary tuberculosis and recent travel to South-East Asia.

The Learning Curve for Pancreaticoduodenectomy: The Experience of a Single Surgeon.

Pancreaticoduodenectomy (PD) is a complex and high-skill demanding procedure often associated with significant morbidity and mortality. However, the results have improved over the past two decades. However, there is a paucity of research concerning the learning curve for PD. Our aim was to report the outcomes of 100 consecutive PDs representing a single surgeon's learning curve and to depict the factors that influenced the learning process. We reviewed the first 121 PDs performed at our academic center (2013-2019) by a single surgeon; 110 were PDs (5 laparoscopic and 105 open) and 11 were total PDs (1 laparoscopic and 10 open). Subsequent statistics was performed on the first 100 PDs, with attention paid to the learning curve and survival rate at 5 years. The data were analyzed comparing the first 50 cases (Group 1) to the last 50 cases (Group 2). The most frequent histopathological tumor type was pancreatic ductal adenocarcinoma (50%). A total of 39% of patients had preoperative biliary drainage and 45% presented with positive biliary cultures. The preferred reconstruction technique included pancreaticogastrostomy (99%), in situ hepaticojejunostomy (70%), and precolic gastro-jejunal anastomosis (88%). Postoperative complications included biliary fistula (1%), pancreatic fistula (8%), pancreatic stump bleeding (4%), and delayed gastric emptying (13%). The mean operative time decreased after the first 50 cases (p < 0.001) and blood loss after 60 cases (p = 0.046). R1 resections lowered after 25 cases (p = 0.025). Vascular resections (17%) did not influence the rate of complications (p = 0.8). The survival rate at 5 years for pancreatic adenocarcinoma was 32.93%. Outcomes improve as surgeon experience increases, with proper training being the most important factor for minimizing the impact of the learning curve over the postoperative complications. Analyzing the learning curve from the perspective of a single surgeon is mandatory for accurate statistical results and interpretation.

Applicability of Butterfly Pea Flower Extract as an Alternative Natural Dye in Histopathological Canine Mast Cell Tumor Diagnosis

Applicability of Butterfly Pea Flower Extract as an Alternative Natural Dye in Histopathological Canine Mast Cell Tumor Diagnosis

Histopathological tumour microenvironment score independently predicts outcome in primary operable colorectal cancer.

Colorectal cancer (CRC) is a heterogenous malignancy and research is focused on identifying novel ways to subtype patients. In this study, a novel classification system, tumour microenvironment score (TMS), was devised based on Klintrup-Mäkinen grade (KMG), tumour stroma percentage (TSP), and tumour budding. TMS was performed using a haematoxylin and eosin (H&E)-stained section from retrospective CRC discovery and validation cohorts (n = 1,030, n = 787). TMS0 patients had high KMG, TMS1 were low for KMG, TSP, and budding, TMS2 were high for budding, or TSP and TMS3 were high for TSP and budding. Scores were assessed for association with survival and clinicopathological characteristics. Mutational landscaping and Templated Oligo-Sequencing (TempO-Seq) profiling were performed to establish differences in the underlying biology of TMS. TMS was independently prognostic in both cohorts (p < 0.001, p < 0.001), with TMS3 predictive of the shortest survival times. TMS3 was associated with adverse clinical features including sidedness, local and distant recurrence, higher T stage, higher N stage, and presence of margin involvement. Gene set enrichment analysis of TempO-Seq data showed higher expression of genes associated with hallmarks of cancer pathways including epithelial to mesenchymal transition (p < 0.001), IL2 STAT5 signalling (p = 0.007), and angiogenesis (p = 0.017) in TMS3. Additionally, enrichment of immunosuppressive immune signatures was associated with TMS3 classification. In conclusion, TMS represents a novel and clinically relevant method for subtyping CRC patients from a single H&E-stained tumour section.

Astragaloside IV-PESV inhibits prostate cancer tumor growth by restoring gut microbiota and microbial metabolic homeostasis via the AGE-RAGE pathway.

Prostate cancer (PCa) is becoming the most common malignancy in men worldwide. We investigated the effect of astragaloside IV combined with PESV on the gut microbiota and metabolite of PCa mice and the process of treating PCa. Nude mice were genetically modified to develop tumors characteristic of PCa. The treatment of PCa mice involved the administration of a combination of astragaloside IV and peptides derived from scorpion venom (PESV). Feces were collected for both 16S rDNA and metabolic analysis. Fecal supernatant was extracted and used for fecal transplantation in PCa mice. Tumor development was observed in both PCa mice and nude mice. Tumor histopathology was examined, and the expression of inflammatory factors and the AGE-RAGE axis in PCa tissues were analyzed. PCa mice treated with Astragaloside IV in combination with PESV showed a significant reduction in tumor volume and weight, and stabilization of gut microbiota and metabolites. At the Genus level, significant differences were observed in Porphyromonas, Corynebacterium, Arthromitus and Blautia, and the differential metabolites were PA16_016_0, Astragaloside+, Vitamin A acid, Nardosinone, a-Nortestoster, D-Pantethine, Hypoxanthine, Pregnenolone, cinnamic acid, Pyridoxa, Cirtruline and Xanthurenate. There was a correlation between gut microbiota and metabolites. After the fecal transplantation, tumor growth was effectively suppressed in the PCa mice. Notably, both the mRNA and protein levels of the receptor for advanced glycation end products (RAGE) were significantly decreased. Furthermore, the expression of inflammatory factors, namely NF-κB, TNF-α, and IL-6, in the tumor tissues was significantly attenuated. Conversely, upregulation of RAGE led to increased inflammation and reversed tumor growth in the mice. Astragaloside IV combined with PESV could treat PCa by intervening in gut microbiota composition and metabolite by targeting RAGE.

Abstract LB220: Farnesyltransferase inhibitors show synergistic anticancer effects in combination with novel KRAS G12C inhibitors

Abstract Background. Farnesyltransferase inhibitors (FTI) failed as monotherapies for various cancer types until the discovery of their potency in HRAS mutant human head and neck and bladder cancers. On the other hand, RAS mutant cancers have been a great challenge for cancer research until the discoveries and approvals of several KRAS-G12C allele specific inhibitors. However, G12C inhibitors were effective mainly in lung cancer and de novo and acquired resistance prompted the development of various combinational modalities including immunotherapy as well as SOS- and SHP2-inhibitors. Based on in-silico analysis of drug sensitivities of KRAS mutant cancer cell lines treated with various drugs including FTIs, we have explored the possibility of the combination of FTIs with KRAS inhibitors.Methods. Clinically approved farnesyl-transferase inhibitors (tipifarnib and lonafarnib) were combined with, novel KRAS G12C inhibitors (sotorasib and adagrasib) using human lung-, pancreatic and colorectal- adenocarcinoma cells in vitro and in vivo. Antitumoral effects were evaluated for cell proliferation, apoptosis and migratory activity. Mechanisms of action were investigated by immunoblot analyzes of various farnesylated proteins, RAS activation and signaling, videomicroscopy and also by histopathology of xenograft tumors. Results. Synergistic anticancer effects were observed upon the combination of FTIs with G12C inhibitors in KRAS G12C mutant human cancer cell lines in vitro. We found that the combination interfered with the compensatory re-activation of HRAS, farnesylation of RHEB in the PI3K/mTOR pathway and lamin. Furthermore, we observed enhanced efficacy of sotorasib upon combination with tipifarnib in the xenograft models of lung adenocarcinoma affecting mitotic- and apoptotic rates and inducing necrosis.Discussion. Our findings suggest the potential clinical applicability of the combination of KRAS-G12C inhibitors and farnesyl-transferase inhibitors. Furthermore, our preliminary data suggest that the synergistic effect of FTIs on KRAS-G12C inhibitors can be projected to G12D inhibitors as well. Citation Format: Jozsef Timar, Marcell Baranyi, Eszter Molnar, Ivan Randelovic, Mihaly Cserepes, Jozsef Tovari, Balazs Hegedus. Farnesyltransferase inhibitors show synergistic anticancer effects in combination with novel KRAS G12C inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB220.

Abstract LB216: Static and microfluidic platforms for novel therapeutic testing in high-grade serous ovarian cancer

Abstract Background: High-Grade Serous Ovarian Cancer (HGSOC) is the most lethal OC type because of its silent progression and lack of specific markers for early detection. In this context, the timely initiation of effective treatment is imperative to prevent disease progression extending life expectancy. However, responses to treatment can vary significantly among individuals, presenting clinical challenges in selecting effective treatments, necessitating the interpretation of molecular and genomic data of the patient on a case-by-case basis. The aim of this study is to establish a highly sensitive platform, implemented with microfluidic technology, to predict patient drug responses with the goal of assisting oncologists in shaping effective treatments. Moreover, validating this platform through a retrospective study, enabling the development of innovative drugs. Methods: In this work, patient-derived ovarian cancer organoids (PDOs) were engineered for drug screening and twenty FDA approved drugs were assessed on seven PDOs derived from both primary tumors and ascites. The fidelity of PDOs in reproducing the histopathology of the primary tumour was confirmed by immunohistochemistry. Proteomics and repeated screening on high- and low-passage PDOs confirmed the reliability of the platform over time. Furthermore, to bridge the gap between static systems and the dynamic of human tumours, a microfluidic platform was employed and using fluorescence microscopy the patients' drug sensitivity was predicted (PMID: 37143603). Results: PDOs were able to replicate patients' response to the drug in a retrospective study and surprisingly, in some cases, to predict resistance to certain drugs administered on the basis of strong, clinically validated predictive biomarkers, which proved ineffective in the clinic. The platform could predict innovative therapeutic strategies as demonstrated by inhibiting the activity of Peptidylprolyl Cis/Trans Isomerase, NIMA-Interacting 1 (Pin1), a novel druggable target for OC (PMID: 22322860, 29746956, 30697729). The Pin1 inhibitor (VS10) is effective in a subset of patients resistant to platinum-based chemotherapy and synergize with doxorubicin. Finally, a microfluidic platform fluorescence based, which improved drug penetration in PDOs was developed for efficient and faster drug screening. Conclusions: This study underscores the significance of utilizing engineered PDOs to develop predictive and easy to use platforms that can truly aid oncologists in devising patient-specific treatments while circumventing the use of drugs that, despite strong recommendations, may prove ineffective. Furthermore, these platforms have demonstrated their effectiveness in the development of innovative therapeutics, such as Pin1 inhibitors, which have been proven both effective and safe in animal models, underscoring the need for clinical studies. Acknowledgments: AIRC IG23566 Citation Format: Enrico Cavarzerani, Gloria Saorin, Matteo Mauceri, Isabella Caligiuri, Michele Bartoletti, Vincenzo Canzonieri, Flavio Rizzolio. Static and microfluidic platforms for novel therapeutic testing in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB216.

Abstract LB224: Neoplastic immune mimicry potentiates breast cancer progression

Abstract Dedifferentiation programs are commonly enacted during breast cancer progression where they enable novel cellular phenotypes. Increased cellular plasticity within the neoplastic compartment of tumors correlates with disease aggressiveness, often manifesting as greater resistance to cytotoxic therapies or increased ability to metastasize to distant organs. Here we report that subpopulations of ostensibly stem-like neoplastic breast epithelial cells express canonical leukocyte cell surface receptor proteins, and have named this unique cellular program ‘immune mimicry’ (IM). We have documented neoplastic cells engaging in IM by examination of histopathological breast tumor specimens and their derived cell lines, public human breast tumor single-cell RNA-seq datasets, and in murine transgenic and cell line-derived mammary cancer models. Immune-mimicked neoplastic cells harbor hallmarks of dedifferentiation and appear enriched for developing aggressive and high-grade tumors. Experimental studies with breast cancer cell lines revealed that neoplastic cells expressing leukocyte surface features are elicited by growth-arresting conditions, such as conventional cytotoxic chemotherapeutic treatments and during metastatic dissemination in mice. In addition, using proof-of-concept studies, we leveraged the canonical leukocyte activation marker CD69, to demonstrate how its expression by neoplastic epithelial cells confers a proliferative advantage under low-density conditions. We conclude that neoplastic breast epithelial cells expressing leukocyte surface receptors may signify a particularly malignant and tumor-initiating cell state. Moving forward, neoplastic IM will be evaluated for prognostic utility in breast cancer to determine whether this unique cell state stratifies patients with increased risks for tumor recurrence and metastasis. The authors acknowledge NIH/NCI (K00 CA212132, T32 CA254888, P30 CA069533), the Collins Medical Trust, the Susan G Komen Foundation, and the National Foundation for Cancer Research for funding. Citation Format: Eric B. Berens, Sokchea Khou, Elaine Huang, Amber Hoffman, Briana Johnson, Zena Werb, Laura M. Heiser, Lisa M. Coussens. Neoplastic immune mimicry potentiates breast cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB224.

Chemotherapeutic potential of betanin/capecitabine combination targeting colon cancer: experimental and bioinformatic studies exploring NFκB and cyclin D1 interplay.

Introduction: Betanin (C₂₄H₂₆N₂O₁₃) is safe to use as food additives approved by the FDA with anti-inflammatory and anticancer effects in many types of cancer cell lines. The current experiment was designed to test the chemotherapeutic effect of the combination of betanin with the standard chemotherapeutic agent, capecitabine, against chemically induced colon cancer in mice. Methods: Bioinformatic approach was designed to get information about the possible mechanisms through which the drugs may control cancer development. Five groups of mice were assigned as, (i) saline, (ii) colon cancer, (iii) betanin, (iv) capecitabine and (v) betanin/capecitabine. Drugs were given orally for a period of six weeks. Colon tissues were separated and used for biological assays and histopathology. Results: In addition, the mRNA expression of TNF-α (4.58-fold), NFκB (5.33-fold), IL-1β (4.99-fold), cyclin D1 (4.07-fold), and IL-6 (3.55-fold) and protein levels showed several folds increases versus the saline group. Tumor histopathology scores in the colon cancer group (including cryptic distortion and hyperplasia) and immunostaining for NFκB (2.94-fold) were high while periodic-acid Schiff staining demonstrated poor mucin content (33% of the saline group). These pathologic manifestations were reduced remarkably in betanin/capecitabine group. Conclusion: Collectively, our findings demonstrated the usefulness of betanin/capecitabine combination in targeting colon cancer and highlighted that betanin is a promising adjuvant therapy to capecitabine in treating colon cancer patients.

The Profile of Sinonasal Tumors with Orbital Involvement in Dr. M. Djamil General Hospital, Padang, Indonesia: A 10-Year Overview

Background: Sinonasal tumors are rare tumors, either malignant or benign, that vary greatly based on the origin and primary tumor location in the sinonasal tract. The close anatomical relationship between the sinonasal tract and the orbital cavity makes orbital involvement very common (50%-80%) in sinonasal tumors, and this indicates a negative prognostic factor in sinonasal malignancy. The purpose of this study is to demonstrate the profile of sinonasal tumors with orbital involvement in our center.&#x0D; Methods: Retrospective study from oncology subdivision files and medical records from January 2011 – December 2020. Collected data including age, gender, the clinical manifestations of orbital involvement, primary location, histopathology, and management of sinonasal tumors.&#x0D; Results: There were 35 patients examined by the oncology subdivision either directly came or consulted from the ENT department, consisting of 18 (51.4%) males and 17 (48.6%) females. The age of patients ranged from 11 to 83 years old. with the most common age groups being 41-50 and 51-60 (25.7% in each age group). The majority of the patients (77.1%) had presented with proptosis. Maxillary sinus was the most common (45.7%) primary site of tumors, and squamous cell carcinoma was the most common (51.4%) histopathology found. Most of the patients (37.1%) were treated with a combination of chemotherapy and radiotherapy.&#x0D; Conclusion: Orbital involvement commonly occurs in malignant sinonasal tumors with proptosis as a major clinical presentation. A combination of chemotherapy and radiotherapy was the most common practice management because the tumors were unresectable at the time of presentation.

Abstract 886: Integrated deep learning model for predicting DNA methylation and tumor types from histopathology in central nervous system tumors

Abstract Precision in diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal patient treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are data-driven means to enhance diagnostic accuracy, but this technique is expensive, time-consuming, and not yet routinely available. To address this, we developed DEPLOY, a deep-learning model that predicts 10 major categories of CNS tumors from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from histopathology slide images (‘direct model’); the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification (‘indirect model’); and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicted beta values from histopathology images, suggesting that application of inferred methylation data is a promising approach for deep learning histopathology-based classifiers. Using a 10-class model trained on an internal dataset, we apply this model on two independent external test datasets of 1,522 and 348 cases, achieving top-1 accuracies of 96% and 94%, respectively on samples which are predicted with high confidence. Taken together, DEPLOY could assist pathologists in diagnosing CNS tumors, in an equitable very low-cost manner, within a clinically relevant short time frame. Citation Format: Eldad David Shulman, Danh-Tai Hoang, Rust Turakulov, Zied Abdullaev, Omkar Singh, Emma M. Campagnolo, Eric A. Stone, MacLean P. Nasrallah, Eytan Ruppin, Kenneth Aldape. Integrated deep learning model for predicting DNA methylation and tumor types from histopathology in central nervous system 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 886.

Abstract 1880: Ecubectedin and PM54 demonstrate antitumor activity in patient-derived xenograft models of soft tissue sarcoma

Abstract Objective: Soft tissue sarcoma (STS) is a heterogenous group of rare, malignant tumors arising from mesenchymal tissue. Doxorubicin (DOX)-based chemotherapy is the standard for advanced or metastatic STS, despite low response rates and poor disease control. We explored the antitumor activity of two novel compounds, ecubectedin (ECU; PM14) and PM54 (PharmaMar), in two patient-derived xenograft (PDX) models of STS, leiomyosarcoma (LMS) and CIC-rearranged sarcoma (CRS). Mode of action of ECU and PM54 is similar to lurbinectedin (LUR), inhibiting oncogenic transcription by eviction of oncogenic transcription factors from gene promotors’ recognition sequences, while inducing the generation of double strand breaks through DNA adduct formation. Methods: Female NMRI nu/nu mice (n=104) were transplanted bilaterally with STS PDX: UZLX-STS134 (CRS) and UZLX-STS22_2 (LMS). Xenografted mice were randomized to six treatment groups: 1) vehicle (VEH) (5% dextrose) 5 mL/kg once weekly (QW) intravenously (IV); 2) DOX 5 mg/kg QW IV; 3) trabectedin (TRA) 0.15 mg/kg QW IV; 4) LUR 0.18 mg/kg QW IV; 5) ECU 1.2 mg/kg QW IV; 6) PM54 1.2 mg/kg QW IV. Treatment lasted 16 days and antitumor activity was assessed by tumor volume (TV) analysis, histopathology and western blot. The Mann-Whitney U test was used to compare groups, the Wilcoxon test to compare to baseline. Results: ECU and PM54 caused TV shrinkage in UZLX-STS134, while TV in other groups grew significantly on day 16 (Table 1). VEH treatment led to the largest TV increase on day 16, compared to any treatment. PM54 treatment showed TV stabilization in UZLX-STS22_2, and significantly smaller tumors than VEH and TRA treated tumors (p&amp;lt;0.05 and p&amp;lt;0.01, respectively). Histopathological evaluation corroborate the results from the relative TV analysis. Conclusion: Novel drugs exhibit promising results in the PDX models tested, supporting ongoing exploration in additional PDX models of synovial sarcoma and dedifferentiated liposarcoma. Table 1: TV change on day 16 versus baseline, and comparison of proliferative and apoptotic activity Tumor volume change Proliferative activity (pHH3) Apoptotic activity (cPARP) Subtypes UZLX-STS134 UZLX-STS22_2 UZLX-STS134 UZLX-STS22_2 UZLX-STS134 UZLX-STS22_2 VEH(5 ML/kg) 387%*** 349%** n/a n/a n/a n/a DOX (5 mg/kg/QW IV) 177%*** 243%** ↓*** ↓ ↑** ↑ TRA(0.15 mg/kg/QW IV) 230%** 254%*** ↓** ↓** ↑** ↑*** LUR(0.18 mg/kg/QW IV) 202%** 232%** ↓*** ↓*** ↑*** ↑** ECU(1.2 mg/kg/QW IV) 41%*** 181%** ↓*** ↓*** ↑*** ↑*** PM54 (1.2 mg/kg/QW IV) 76%*** 162% ↓*** ↓*** ↑*** ↑ Citation Format: Daniël Gorgels, Agnieszka Wozniak, Chao-Chi Wang, Pablo M. Avilés, Maria J. Guillen, Carmen Cuevas, Patrick Schöffski. Ecubectedin and PM54 demonstrate antitumor activity in patient-derived xenograft models of soft tissue sarcoma [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 1880.

Abstract 4919: AI-enabled hit selection of drug screening on human pancreatic cancer organoids

Abstract Cancer remains one of the leading causes of death in the 21st century. Despite the latest advances in oncology, most cancer patients lack tailored therapeutic approaches with lasting benefit. Measuring the impact of anticancer compounds and their combinations is only possible on ex vivo assays. To this end, patient-derived organoids (PDOs) have been proposed as viable and efficient models for ex vivo testing. PDOs show long-term expansion potential while retaining tumor histopathology as well as cancer gene mutations. However, the translation of organoids in screening applications has so far been hampered by the lack of homogeneity and difficulties in handling and automation. Moreover, organoids are typically randomly distributed across the culture which complicates imaging and images analyses. To overcome these challenges, we set up a compound screening workflow with PDOs using Gri3D platform, comprising plates with micro-cavities suitable for high-throughput and reproducible organoid culture. Based on a standard 96 microtiter plate, each well contains a microwell array patterned in a cell repellent hydrogel. On Gri3D®, organoids are robustly generated in the microwells and are located in the same imaging plane. This greatly facilitates quantitative analyses in high content image-based screens. Furthermore, the pipetting port enables automation of cell seeding, media exchange and compound incubation with liquid-handlers, thus increasing assay reproducibility. In the presented work, we exposed human pancreatic cancer PDOs to a panel of anti-cancer compounds at different doses and followed their response to the drugs using viability dyes Calcein AM (live stain) and Ethidium Homodimer-1 (dead stain) with high-content confocal imaging. Using an AI-based approach, we efficiently detected each single organoid and extracted phenotypic features from all three channels (TL, live stain and dead stain) which correlate with cytotoxicity. The extracted features (more than 100) were first dimensionally reduced to 3 components using either PCA or UMAP, the treatments were then visualized in 3D scatter plots, ranked and clustered using machine learning. The data suggests that the compound treatment Palbociclib 50uM has significant cytotoxicity effects similar to the positive control, which is consistent with the traditional live/dead analysis. The AI approach demonstrates feasibility to perform drug screening in a robust and un-biased data analysis approach. Citation Format: Zhisong Tong, Angeline Lim, Marine Meyer, Maria Clapes, Oksana Sirenko, Nathalie Brandenberg. AI-enabled hit selection of drug screening on human pancreatic cancer organoids [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 4919.

Abstract 7302: Effect of estrogen receptor modulator bazedoxifene on progression of carcinogen induced bladder cancer in female F344 rats

Abstract Bladder Cancer (BC) is the second most common genitourinary cancer with high recurrence and mortality rate due to metastatic muscle invasive BC (MIBC). An estimated 82,290 adults in the United States will be diagnosed with BC and one-fifth of the patients will die with this cancer in 2023. Sex disparity of BC is well known with 4 times higher risk in men, but women are more likely to die from it than men. Studies suggest that estrogen receptor (ER)-α and ER-β are over expressed in 18% and 63% of bladder tumors and associated with highly proliferative tumors and reduced overall survival. Hence, ER signaling is considered an important target for intercepting BC. Since the majority of BCs are non-invasive at diagnosis, developing agents that block BC progression may be beneficial for clinical translation. Bazedoxifene (BAZ), a clinically approved second generation SERM, is a co-repressor for both the ER-α and ER-β receptors, and it is a competitive inhibitor of 17-β-estradiol. In this study, BAZ was tested for toxicity and efficacy in an N-butyl-N-(4-hydroxybutyl)nitrosamine (BBN)-induced BC rat model. Female F344 rats are administered carcinogen BBN (150mg x twice a week) for 8 weeks to induce BC. For toxicity evaluation, 5 doses of BAZ were fed (2.5 ppm to 12.5 ppm in diet) to BBN treated rats (n=6) for 10 weeks. After termination, serum, various organs, and bladder tissues were evaluated for toxicity biomarkers and histopathology. For efficacy study, Female F344 rats (8 weeks of age) were (n=24) administered BBN as stated above. A week later, rats received either control or BAZ (5 ppm and 10 ppm) containing diets for 33 weeks and terminated. Bladders and other major organs were analyzed grossly for size, weight, and visible abnormalities including tumors. Formalin fixed tumor sections were stained and histopathologically graded. Results showed that BBN-exposed rat bladders were significantly larger and heavier due to tumors (0.77±0.10g, Mean±SEM; p&amp;lt;0.0001) as compared to vehicle treated rats’ normal bladders (0.09±0.02g). Bladder tumor histopathology showed transitional cell carcinoma (TCC) and squamous cell carcinomas (SCC) with non-MIBC (NMIBC) and MIBC tumor grades in the vehicle control group. There was no significant difference in bladder weights between the 5 ppm and 10 ppm BAZ-treated vs. control group (p&amp;gt;0.05). However, histopathological evaluation showed ~20% (p&amp;gt;0.05) reduction in papilloma and NMIBC in the treated rats. Importantly, BAZ 5 ppm and 10 ppm treated rats had significantly less MIBC in a dose dependent manner (50%-70% less respectively; p&amp;lt;0.001) compared to control rats. In summary, our study demonstrates chemopreventive efficacy of bazedoxifene in interception of in BBN-induced rat bladder MIBC and warrants further investigation alone and in combination with complementary pathway targeting agents (Supported by NCI-PREVENT program 75N91019D00020-75N91020F00005). Citation Format: Venkateshwar Madka, Gopal Pathuri, Surya P. Singh, Srikanth Chiliveru, Anil Singh, Anh Bao, Nicole Stratton, Clinton J. Grubbs, Shizuko Sei, John Clifford, Brian Cholewa, Chinthalapally V. Rao. Effect of estrogen receptor modulator bazedoxifene on progression of carcinogen induced bladder cancer in female F344 rats [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 7302.

Analyzing the Impact of Oncological Data at Different Time Points and Tumor Biomarkers on Artificial Intelligence Predictions for Five-Year Survival in Esophageal Cancer

AIM: In this study, we use Artificial Intelligence (AI), including Machine (ML) and Deep Learning (DL), to predict the long-term survival of resectable esophageal cancer (EC) patients in a high-volume surgical center. Our objective is to evaluate the predictive efficacy of AI methods for survival prognosis across different time points of oncological treatment. This involves comparing models trained with clinical data, integrating either Tumor, Node, Metastasis (TNM) classification or tumor biomarker analysis, for long-term survival predictions. METHODS: In this retrospective study, 1002 patients diagnosed with EC between 1996 and 2021 were analyzed. The original dataset comprised 55 pre- and postoperative patient characteristics and 55 immunohistochemically evaluated biomarkers following surgical intervention. To predict the five-year survival status, four AI methods (Random Forest RF, XG Boost XG, Artificial Neural Network ANN, TabNet TN) and Logistic Regression (LR) were employed. The models were trained using three predefined subsets of the training dataset as follows: (I) the baseline dataset (BL) consisting of pre-, intra-, and postoperative data, including the TNM but excluding tumor biomarkers, (II) clinical data accessible at the time of the initial diagnostic workup (primary staging dataset, PS), and (III) the PS dataset including tumor biomarkers from tissue microarrays (PS + biomarkers), excluding TNM status. We used permutation feature importance for feature selection to identify only important variables for AI-driven reduced datasets and subsequent model retraining. RESULTS: Model training on the BL dataset demonstrated similar predictive performances for all models (Accuracy, ACC: 0.73/0.74/0.76/0.75/0.73; AUC: 0.78/0.82/0.83/0.80/0.79 RF/XG/ANN/TN/LR, respectively). The predictive performance and generalizability declined when the models were trained with the PS dataset. Surprisingly, the inclusion of biomarkers in the PS dataset for model training led to improved predictions (PS dataset vs. PS dataset + biomarkers; ACC: 0.70 vs. 0.77/0.73 vs. 0.79/0.71 vs. 0.75/0.69 vs. 0.72/0.63 vs. 0.66; AUC: 0.77 vs. 0.83/0.80 vs. 0.85/0.76 vs. 0.86/0.70 vs. 0.76/0.70 vs. 0.69 RF/XG/ANN/TN/LR, respectively). The AI models outperformed LR when trained with the PS datasets. The important features shared after AI-driven feature selection in all models trained with the BL dataset included histopathological lymph node status (pN), histopathological tumor size (pT), clinical tumor size (cT), age at the time of surgery, and postoperative tracheostomy. Following training with the PS dataset with biomarkers, the important predictive features included patient age at the time of surgery, TP-53 gene mutation, Mesothelin expression, thymidine phosphorylase (TYMP) expression, NANOG homebox protein expression, and indoleamine 2,3-dioxygenase (IDO) expressed on tumor-infiltrating lymphocytes, as well as tumor-infiltrating Mast- and Natural killer cells. CONCLUSION: Different AI methods similarly predict the long-term survival status of patients with EC and outperform LR, the state-of-the-art classification model. Survival status can be predicted with similar predictive performance with patient data at an early stage of treatment when utilizing additional biomarker analysis. This suggests that individual survival predictions can be made early in cancer treatment by utilizing biomarkers, reducing the necessity for the pathological TNM status post-surgery. This study identifies important features for survival predictions that vary depending on the timing of oncological treatment.