Translational Cancer Research Research Articles

RAB4A is a master regulator of cancer cell stemness upstream of NUMB–NOTCH signaling

Cancer stem cells (CSCs) are a group of specially programmed tumor cells that possess the characteristics of perpetual cell renewal, increased invasiveness, and often, drug resistance. Hence, eliminating CSCs is a major challenge for cancer treatment. Understanding the cellular programs that maintain CSCs, and identifying the critical regulators for such programs, are major undertakings in both basic and translational cancer research. Recently, we have reported that RAB4A is a major regulator of epithelial-to-mesenchymal transition (EMT) and it does so mainly through regulating the activation of RAC1 GTPase. In the current study, we have delineated a new signaling circuitry through which RAB4A transmits its control of cancer stemness. Using in vitro and in vivo studies, we show that RAB4A, as the upstream regulator, relays signal stepwise to NUMB, NOTCH1, RAC1, and then SOX2 to control the self-renewal property of multiple cancer cells of diverse tissue origins. Knockdown of NUMB, or overexpression of NICD (the active fragment NOTCH1) or SOX2, rescued the in vitro sphere-forming and in vivo tumor-forming abilities that were lost upon RAB4A knockdown. Furthermore, we discovered that the chain of control is mostly through transcriptional regulation at every step of the pathway. The discovery of the novel signaling axis of RAB4A–NUMB–NOTCH–SOX2 opens the path for further expansion of the signaling chain and for the identification of new regulators and interacting proteins important for CSC functions, which can be explored to develop new and effective therapies.

EP.06G.09 Harnessing Real-World Data for Translational Research in Lung Cancer: MD Anderson Thoracic GEMINI Program

EP.06G.09 Harnessing Real-World Data for Translational Research in Lung Cancer: MD Anderson Thoracic GEMINI Program

Post-surgery sequelae unrelated to disease progression and chemotherapy revealed in follow-up of patients with stage III colon cancer

We studied the poorly-known dynamics of circulating DNA (cir-nDNA), as monitored prospectively over an extended post-surgery period, in patients with cancer. On patients with stage III colon cancer (N=120), using personalised molecular tags we carried out the prospective, multicenter, blinded cohort study of the post-surgery serial analysis of cir-nDNA concentration. 74 patients were included and 357 plasma samples tested. During post-operative follow-up, the patients' median cir-nDNA concentration was greater (P<0.0001 in the [43-364 days range]) than both the median value in healthy individuals and the pre-surgery value. These cir-nDNA levels were highly associated with NETs markers (P-value associating MPO and cir-nDNA, and NE and cir-nDNA are 6.6 x 10-17, and 1.9 x 10-7), in accordance with previous reports which indicate that cir-nDNA are NETs by-products. Unexpectedly, in 34 out of 50 patients we found that NETs continued to be formed for an extended duration post-surgery, even in patients without disease progression. Given that this phenomenon was observed in patients without adjuvant CT, and in patients >18 months post-surgery, the data suggest that the persistence of NETs formation is not due to the adjuvant CT. (1), Given the inter-patient heterogeneity, the post-surgery cir-nDNA level cannot be considered a reliable value, and caution must be exercised when determining mutation allele frequency or the mutation status; and (2), specific studies must be undertaken to investigate the possible clinical impact of the persistent, low-grade inflammation resulting from elevated NETs levels, such as observed in these post-surgery patients, given that such levels are known to potentially induce adverse cardiovascular or thrombotic events. This work was supported by the H2020 European ERA-NET grant on Translational Cancer Research (TRANSCAN-2).

Abstract B080: A porcine model of pancreatic ductal adenocarcinoma for human scale translational cancer research

Abstract Pancreatic ductal adenocarcinoma (PDAC) remains a highly fatal form of cancer, requiring urgent advancements in diagnostic and therapeutic strategies. Although PDAC mouse models have been crucial in advancing our comprehension of the disease, they present some limitations in replicating key human PDAC aspects. In this study, we present the development of the first large animal model of pancreatic cancer via Cre activatable mutations in the endogenous KRAS and TP53 genes 1,2. In order to activate these mutations in the pancreas, two Cre driver pig lines expressing Cre recombinase from PTF1A 3 and PDX1 were created. Crossing both Cre lines with pigs carrying latent KRAS G12D and TP53 R167H alleles produced double (KC) and triple (KPC) genetically modified animals. Pathological analyses revealed the presence of inter- and intralobular fibrosis with multifocal acinar-to-ductal metaplasia (ADM), some low-grade PanINs, dysplasia, inflammation and duct obstruction in most of the KPC pigs between 3 to 6 months of age. Interestingly, the majority of these pigs already exhibited local metastasis in the lymph nodes, suggesting that the metastatic potential is established early in the tumorigenic process. Age-matched KC pigs exhibited mainly ADM with dysplasia. Flow cytometry and RNA expression analyses of the established pancreatic tumour primary cells revealed a pronounced epithelial-to-mesenchymal transition (EMT). Moreover, both bulk tumour samples and primary tumour cells showed high expression of the pancreatic cancer stem cell marker CD44, with differential expression of its isoforms, including the major isoform and variants 6 and 9. In addition, histological and molecular analyses revealed notable similarities between pig and human PDAC, including molecular subtypes, neuronal invasion and loss of acinar identity. These findings highlight the unique advantage of the pig PDAC model, that allows longitudinal and multi-regional tumour sampling in the absence of any therapeutic interventions. This makes it a valuable tool for developing new diagnostic and therapeutic approaches that can greatly improve patient outcomes in the long run.

Systematic review and feasibility study on pre-analytical factors and genomic analyses on archival formalin-fixed paraffin-embedded breast cancer tissue

Formalin-fixed paraffin-embedded (FFPE) tissue represents a valuable source for translational cancer research. However, the widespread application of various downstream methods remains challenging. Here, we aimed to assess the feasibility of a genomic and gene expression analysis workflow using FFPE breast cancer (BC) tissue. We conducted a systematic literature review for the assessment of concordance between FFPE and fresh-frozen matched tissue samples derived from patients with BC for DNA and RNA downstream applications. The analytical performance of three different nucleic acid extraction kits on FFPE BC clinical samples was compared. We also applied a newly developed targeted DNA Next-Generation Sequencing (NGS) 370-gene panel and the nCounter BC360® platform on simultaneously extracted DNA and RNA, respectively, using FFPE tissue from a phase II clinical trial. Of the 3701 initial search results, 40 articles were included in the systematic review. High degree of concordance was observed in various downstream application platforms. Moreover, the performance of simultaneous DNA/RNA extraction kit was demonstrated with targeted DNA NGS and gene expression profiling. Exclusion of variants below 5% variant allele frequency was essential to overcome FFPE-induced artefacts. Targeted genomic analyses were feasible in simultaneously extracted DNA/RNA from FFPE material, providing insights for their implementation in clinical trials/cohorts.

CGPA: multi-context insights from the cancer gene prognosis atlas.

Cancer transcriptomic data are used extensively to interrogate the prognostic value of targeted genes, yet basic scientists and clinicians have predominantly relied on univariable survival analysis for this purpose. This method often fails to capture the full prognostic potential and contextual relevance of the genes under study, inadvertently omitting a group of genes we term univariable missed-opportunity prognostic (UMOP) genes. Recognizing the complexity of revealing multifaceted prognostic implications, especially when extending the analysis to include various covariates and thresholds, we present the Cancer Gene Prognosis Atlas (CGPA). This platform greatly enhances gene-centric biomarker research across cancer types by offering an interactive and user-friendly interface for highly customized, in-depth prognostic analysis. CGPA notably supports data-driven exploration of gene pairs and gene-hallmark relationships, elucidating key composite biological mechanisms like synthetic lethality and immunosuppression. It further expands its capabilities to assess multi-gene panels using both public and user-provided data, facilitating a seamless mechanism-to-machine analysis. Additionally, CGPA features a designated portal for discovering prognostic gene modules using curated cancer immunotherapy data. Ultimately, CGPA's comprehensive, accessible tools allow cancer researchers, including those without statistical expertise, to precisely investigate the prognostic landscape of genes, customizing the model to fit specific research hypotheses and enhancing biomarker discovery and validation through a synergy of mechanistic and data-driven strategies.

Neratinib and ado-trastuzumab emtansine for pretreated and untreated human epidermal growth factor receptor 2 (HER2)-positive breast cancer brain metastases: Translational Breast Cancer Research Consortium trial 022

Treatment options for human epidermal growth factor receptor 2 (HER2)-positive breast cancer brain metastases (BCBMs) remain limited. We previously reported central nervous system (CNS) activity for neratinib and neratinib-capecitabine. Preclinical data suggest that neratinib may overcome resistance to ado-trastuzumab emtansine (T-DM1) when given in combination. In Translational Breast Cancer Research Consortium (TBCRC) 022's cohort 4, we examined the efficacy of neratinib plus T-DM1 in patients with HER2-positive BCBM. In this multicenter, phase II study, patients with measurable HER2-positive BCBM received neratinib 160 mg daily plus T-DM1 3.6 mg/kg intravenously every 21 days in three parallel-enrolling cohorts [cohort 4A-previously untreated BCBM, cohorts 4B and 4C-BCBM progressing after local CNS-directed therapy without (4B) and with (4C) prior exposure to T-DM1]. Cycle 1 diarrheal prophylaxis was required. The primary endpoint was the Response Assessment in Neuro-Oncology-Brain Metastases (RANO-BM) by cohort. The overall survival (OS) and toxicity were also assessed. Between 2018 and 2021, 6, 17, and 21 patients enrolled in cohorts 4A, 4B, and 4C. Enrollment was stopped prematurely for slow accrual. The CNS objective response rate in cohorts 4A, 4B, and 4C was 33.3% [95% confidence interval (CI) 4.3% to 77.7%], 35.3% (95% CI 14.2% to 61.7%), and 28.6% (95% CI 11.3% to 52.2%), respectively; 38.1%-50% experienced stable disease for ≥6 months or response. Diarrhea was the most common grade 3 toxicity (22.7%). The median OS was 30.2 [cohort 4A; 95% CI 21.9-not reached (NR)], 23.3 (cohort 4B; 95% CI 17.6-NR), and 20.9 (cohort 4C; 95% CI 14.9-NR) months. We observed intracranial activity for neratinib plus T-DM1, including those with prior T-DM1 exposure, suggesting synergistic effects with neratinib. Our data provide additional evidence for neratinib-based combinations in patients with HER2-positive BCBM, even those who are heavily pretreated.

Abstract IA011: Towards mapping the landscape of cancer vulnerabilities

Abstract I will introduce the Cancer Dependency Map (DepMap) project. This project aims to build a resource to identify the landscape of cancer vulnerabilities by linking molecular alterations of tumors to gene dependencies or drug sensitivities. This resource is being used by scientists around the world and has made significant contributions to basic and translational cancer research. I will describe how we are building DepMap and the multiple components it requires. Additionally, I will discuss ongoing projects to expand DepMap, including screening next-generation models. I will also present how to identify potential therapeutic targets using DepMap data and the emerging types of targets. Lastly, I will highlight a recently identified synthetic lethal target in the ribosome rescue pathway in molecularly defined patient populations, demonstrating the power of DepMap in identifying such targets. Citation Format: Francisca Vazquez. Towards mapping the landscape of cancer vulnerabilities [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA011.

ETHAN: A phase II study comparing different endocrine therapies for male breast cancer.

TPS632 Background: Male breast cancer is a rare disease, and most cases are hormone receptor-positive (HR+). Due to a lack of clinical trials, male breast cancer has historically been treated based on data extrapolated from women. However, there are substantial knowledge gaps in the comparative efficacy, safety, and patient-reported outcomes of endocrine therapies for male breast cancer. While tamoxifen is the current standard of care, additional data are warranted for aromatase inhibitors (AI), gonadal suppression, and cyclin-dependent kinase 4/6 (CDK4/6) inhibitors. Methods: This is an open-label, multicenter, randomized, phase II trial designed to evaluate different endocrine therapies in men with HR+ and human epidermal growth factor receptor 2 (HER2)-negative breast cancer. A total of 60 men will be enrolled across nine (9) sites within the Translational Breast Cancer Research Consortium (TBCRC). Key eligibility criteria include male sex and stage I, II, or III HR+/HER2- breast cancer before surgical resection of the primary tumor and axillary nodes. Key exclusion criteria include prior anti-cancer therapy for the current breast cancer or any other malignancy within the past 12 months, and inflammatory breast cancer. The trial has two phases. The first phase is a window of opportunity component in which newly diagnosed men are randomized 1:1:1 to either tamoxifen (Arm A), anastrozole (Arm B), or anastrozole plus degarelix (Arm C) given for three weeks. The primary endpoint for the window phase is Ki-67 reduction from the baseline diagnostic biopsy to the research biopsy at the end of the window phase. The second phase consists of neoadjuvant treatment, in which the tamoxifen group is randomized 1:1 to tamoxifen (Arm D) versus tamoxifen plus abemaciclib (Arm E), and the anastrozole alone (Arm B) and anastrozole plus degarelix (Arm C) groups are merged and then randomized 1:1 to anastrozole plus degarelix (Arm F) versus anastrozole plus degarelix plus abemaciclib (Arm G). The duration of the neoadjuvant phase is four (4) months, and the primary endpoint of this phase is residual cancer burden (RCB) index at time of surgery. The trial is powered for the RCB endpoint in a 2 x 2 factorial design to detect a 0.6 unit decrease in RCB index with 80% power and alpha=10%. For the Ki-67 endpoint, we assume an approximately 50% reduction in Arms A and B; Arm C will be of interest if it leads to ≥80% reduction in Ki-67. Secondary endpoints include: estradiol and testosterone levels at baseline, end of window, and during neoadjuvant phase; preoperative endocrine prognostic index (PEPI) score at surgery; adverse events; and patient-reported outcomes (including quality of life). Tumor tissue will be collected for correlative analyses. The study opened to enrollment at Dana-Farber in October 2023, and additional sites will open in 2024. Clinical trial information: NCT05501704 .

Regulation of the Function and Expression of EpCAM.

The epithelial cell adhesion molecule (EpCAM) is a single transmembrane protein on the cell surface. Given its strong expression on epithelial cells and epithelial cell-derived tumors, EpCAM has been identified as a biomarker for circulating tumor cells (CTCs) and exosomes and a target for cancer therapy. As a cell adhesion molecule, EpCAM has a crystal structure that indicates that it forms a cis-dimer first and then probably a trans-tetramer to mediate intercellular adhesion. Through regulated intramembrane proteolysis (RIP), EpCAM and its proteolytic fragments are also able to regulate multiple signaling pathways, Wnt signaling in particular. Although great progress has been made, increasingly more findings have revealed the context-specific expression and function patterns of EpCAM and their regulation processes, which necessitates further studies to determine the structure, function, and expression of EpCAM under both physiological and pathological conditions, broadening its application in basic and translational cancer research.

A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a comprehensive database of inorganic NP research is not currently available, it is crucial for developing effective cancer therapies. In this context, machine learning (ML) has emerged as a transformative tool, but its adaptation to nanomedicine is hindered by inexistent or small datasets. Here we assembled a large database of inorganic NPs, comprising experimental datasets from 745 preclinical studies in cancer nanomedicine. Using descriptive statistics and explainable ML models we mined this database to gain knowledge of inorganic NP design patterns and inform future NP research for cancer treatment. Our analyses suggest that NP shape and therapy type are prominent features in determining in vivo efficacy, measured as a percentage of tumour reduction. Moreover, our database provides a large-scale open-access resource for discriminative ML that the broader nanotechnology community can utilize. Our work blueprints data mining for translational cancer research and offers evidence for standardizing NP reporting to accelerate and de-risk inorganic NP-based drug delivery, which may help to improve patient outcomes in clinical settings.

The importance of basic and translational research in caring for children with malignant solid tumors in Latin America.

Basic and translational research in pediatric cancer are essential to improve patient care. To critically assess the developments achieved in these areas in Latin America, we systematically reviewed information published between 2013 and 2023. Studies of basic and translational research performed by investigators in Latin America evaluating pediatric malignant solid and central nervous system tumors were retrieved from PubMed. Original articles published in English between 2013 and 2023 were included. Collaborations among Latin American authors or among Latin American authors working with researchers from other continents were also included. Studies were excluded if they focused only on adults or on basic research in tumor biology not specifically related to the tumor types analyzed in this review. A total of 550 articles were retrieved, but after removal of duplicates, 514 articles were included in the analysis, the majority of which were authored by researchers affiliated with institutions in Argentina, Brazil and Mexico. These countries also had the highest number of collaborations on original articles published with authors from Europe and North America. Argentina had the highest number of collaborations on original publications, with coauthors from Brazil and Uruguay. The median impact factor of the 244 journals in which articles were published was 3.5. The most commonly studied tumors were osteosarcomas, neuroblastomas and medulloblastomas; the most commonly studied areas were molecular analysis, tumor cell biology and biomarkers. In Latin America, research in pediatric oncology is on the agenda, despite a notable disparity in publication rates and frequency of collaboration between countries. There is a need to strengthen scientific collaboration within Latin America and with countries from other continents to promote research and to develop novel treatment strategies that reflect the local needs of children in Latin America who have solid tumors and brain cancer.

Abstract PO2-20-01: The STOP-HER2 Trial: A Phase 2 Study of Stopping Trastuzumab - Outcomes in Patients with HER2+ Metastatic Breast Cancer (TBCRC 062)

Abstract BACKGROUND: Anti-HER2 therapies have transformed the trajectory for patients with HER2-positive (HER2+) MBC. A subset of patients with HER2+ MBC do exceptionally well and remain on maintenance anti-HER2 therapy for many years. However, current therapy is non-curative and patients are treated indefinitely. While these therapies often are well-tolerated, they may cause significant toxicities, are expensive, and typically require frequent infusion and provider visits. Case reports and retrospective series demonstrate that some patients may do well after stopping anti-HER2 treatment. We currently lack prospective data on the likelihood of clinical impact of successful treatment discontinuation, outcomes among patients who progress and restart HER2-directed therapy, and tools to predict who may safely stop therapy. In this study, we will enroll pts with an exceptional response to anti-HER2 therapy. Pts may elect to either continue or stop anti-HER2 therapy and will be followed clinically and radiographically on a protocol-specified schedule. Considering the central role of patients in choosing the study intervention arm, and the unique nature of stopping therapy as a treatment intervention, patient advocates have been deeply involved in the study design to ensure patient concerns are being heard and addressed. We will retrospectively assess minimal residual disease (MRD), measured in plasma, as a biomarker of ongoing response, in a step toward shifting the treatment paradigm for pts with HER2+ MBC. METHODS: STOP-HER2 is a prospective, non-randomized, phase II, multicenter study of either continuation (cohort 1) or cessation (cohort 2) of anti-HER2 therapy in exceptional responders with HER2+ MBC. Eligible patients must have biopsy-proven HER2+ MBC by ASCO/CAP guidelines and must have been receiving first-line anti-HER2 therapy for MBC for at least 3 years without evidence of progressive disease (PD) as determined by the treating investigator. Patients with prior brain-only PD or oligo-PD outside the brain are eligible at least 2 years after local treatment to the central nervous system (CNS) and in absence of subsequent PD. Up to fifty-two participants will be enrolled into cohort 2, and an additional thirty participants enrolled into the cohort 1, at 10 US sites within the Translational Breast Cancer Research Consortium. Co-primary endpoints are the 1-year progression-free survival (PFS) in cohorts 2 and 1, separately. Secondary endpoints include the clinical benefit rate upon re-initiation of anti-HER2 therapy for patients in cohort 2 experiencing PD after treatment discontinuation; and 3-year overall survival in both cohorts. Correlative endpoints include MRD status at baseline and the correlation between MRD dynamics and outcomes. Patient-reported outcomes will be collected and analyzed, including quality of life, illness intrusiveness, financial toxicity, anxiety, and decision regret. The study will use a two-stage design to assess the primary objective of estimating the rate of participants who are free of progression at one year after discontinuing anti-HER2 therapy. If 50% or less are free of progression at one year, stopping HER2 therapy would not be considered a viable treatment plan (null hypothesis). The study is designed to have 80% power to reject the null hypothesis at the 10% type I error rate when 68% of exceptional responders are free of progression at one year after stopping HER2 therapy. STOP-HER2 began enrollment in Q2 2023 (NCT05721248). Citation Format: Heather Parsons, Kathryn Ruddy, Stefania Morganti, Karen Smith, Victoria Attaya, Eliza Kallfelz, Michelle DeMeo, Jamie LaScala, Shirley Mertz, Teri Pollastro, Patricia Spears, Adam Brufsky, Chau Dang, Susan Dent, Ahmed Elkhanany, WIlliam Gwin, Ciara O'Sullivan, Kathy Miller, Sara Nunnery, Elaine Walsh, Anna Maria Storniolo, Sara Tolaney, Nabihah Tayob, Antonio Wolff, Eric Winer, Mothaffar Rimawi, Ian Krop, Nancy Lin. The STOP-HER2 Trial: A Phase 2 Study of Stopping Trastuzumab - Outcomes in Patients with HER2+ Metastatic Breast Cancer (TBCRC 062) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-20-01.

Abstract PS03-07: Morphometric signature identifies ductal carcinoma in situ of the breast with low risk of progression to invasive breast cancer

Abstract Background. Ductal carcinoma in situ (DCIS) is a frequently found precursor of invasive breast cancer (IBC). However, the majority of DCIS will never progress to IBC. As we cannot distinguish yet which DCIS will remain indolent (‘harmless’) from those that might progress in the future to IBC, almost all women with DCIS are intensively treated by surgery, often followed by radiotherapy. This brings an urgent clinical need to learn distinguishing harmless from potentially progressive DCIS to save many women with indolent DCIS the burden of unnecessary overtreatment. Aim. We aimed to investigate if the geometry and spatial configuration of DCIS ducts in Hematoxylin-Eosin (H&amp;E) stained tissue sections are related to the risk of progression of DCIS to ipsilateral IBC (iIBC). Methods. We obtained data from a population-based cohort of women diagnosed with primary DCIS between 1989 and 2004 in the Netherlands, treated with breast conserving surgery (BCS) only and a median follow-up time of 12 years. A nested case-control study (n=689) was designed in which patients diagnosed with iIBC recurrences during follow-up were considered as “cases” (n= 226) and those with no subsequent iIBC as “controls” (n=463). The DCIS and stroma regions were digitally annotated on H&amp;E-stained whole slide images (WSIs) by a pathologist as ground truth for the deep learning neural network of HALO AI module (IndicaLabs). We developed a computational pipeline to automatically detect and measure stroma areas, DCIS ducts, and the nucleus of their cells. We validated the accuracy of DCIS detection in H&amp;Es WSIs from an external study, in which DCIS regions were digitally annotated by an independent pathologist (Translational Breast Cancer Research Consortium, TBCRC). We classified cases and controls according to morphological measurements using logistic ridge regression with double-loop cross-validation, followed by hierarchical clustering. The risk of subsequent iIBC after primary DCIS diagnosis was evaluated by multivariate Cox proportional hazards models. Results. The accuracy of DCIS detection performed by the computational pipeline was compared with pathologist annotations in 20 slides from the TBCRC study. Results showed a satisfactory DCIS overlap area agreement of 0.76 (0.68 – 0.83). We applied the DCIS computational pipeline on the case-control series. We obtained 15 morphological measurements for each DCIS duct, such as duct area, cell density, distance between ducts, average nucleus area, etc. We calculated 8 distribution parameters from each measurement in each WSI, including median and range. After leaving out redundant variables, 55 unique morphometric variables were obtained, representing the heterogeneity of DCIS ducts per WSI. The c lassifier revealed a median area-under the curve (AUC) of 0.66 (0.55-0.77) to predict 5-years free of iIBC, 0.59 (0.50-0.67) to predict 10-years and 0.60 (0.52-0.68) to predict 15-years. The 30 variables with the highest association with outcome were used to build four morphometric signatures. Signature number 1, which is characterized by lesions with small-sized ducts, a lower number of cells and a lower DCIS/stroma area ratio, showed a significant lower risk of developing iIBC compared to the other three signatures in a multivariate Cox regression model including grade, ER, COX-2 and HER2 expression: HR = 0.56 (0.28-0.78 95%CI). Conclusion. We developed a computational pipeline able to detect and measure DCIS ducts in H&amp;E WSIs with high accuracy and reproducibility. DCIS lesions presenting the morphometric signature of small-sized DCIS ducts have a very low chance to progress to invasive breast cancer. After successful validation, our morphometric method will serve as a robust and easy to implement biomarker for de-escalation strategies in DCIS, and as such, could limit unnecessary overtreatment in the near future. Citation Format: Marcelo Sobral-Leite, Simon Castillo, Shiva Vonk, Xenia Melillo, Noomie Lam, Brandi de Bruijn, Yeman Hagos, Joyce Sanders, Mathilde Almekinders, Lindy Visser, Emilie Groen, Carolien Van der Borden, Petra Kristel, Ercan Caner, Leyla Azarang, Yinyin Yuan, Renee Menezes, Esther Lips, Jelle Wesseling, Grand Challenge PRECISION Consortium. Morphometric signature identifies ductal carcinoma in situ of the breast with low risk of progression to invasive breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS03-07.

Abstract PO5-26-11: The Breast Cancer Research Foundation Drug Research Collaborative – A unique and innovative model for industry-funded, academically driven research to advance the field of breast cancer

Abstract The Breast Cancer Research Foundation (BCRF) is committed to preventing and curing breast cancer through groundbreaking research. In pursuit of this mission, the BCRF launched the Drug Research Collaborative (DRC) in 2016—a pioneering program designed to bridge the gap between academic investigators and access to investigational therapies, thereby fostering greater academic-driven research in breast cancer. The DRC's primary objective is to fund independent, innovative, and high-quality investigator-initiated trials (IITs) and pre-clinical/translational research projects. In conventional drug development, industry-sponsored registration trials play a crucial role, leaving limited resources and scope for exploratory and translational IITs that fall outside the industry's drug approval strategy. Additionally, industry-funded IIT research faces challenges such as reputational risks, perceived influence during internal review processes, intellectual property (IP) concerns, and logistics/program management burdens. The BCRF-DRC program addresses these challenges by issuing requests for proposals to generate creative and unbiased ideas, which are then vetted through an academic review process involving leading breast cancer experts. The most promising research projects are selected for further advancement. The BCRF-DRC program is facilitated by the BCRF research staff, providing project management, while the Translational Breast Cancer Research Consortium (TBCRC), founded by the BCRF and also supported by Susan G. Komen, supports the clinical trial aspects of the program. Since its inception, the BCRF-DRC has expanded from one to three industry partners, securing a total funding of $25 million for 15 projects, including seven clinical trials and eight pre-clinical projects. This abstract reports on the ongoing progress and outcomes achieved by these three programs. The BCRF-DRC represents a revolutionary paradigm in research funding and collaboration by harnessing the collective power of industry partners, philanthropic organizations, and academic institutions. Through this collaborative effort, the BCRF-DRC provides a unique platform for researchers to accelerate the translation of scientific discoveries into effective clinical interventions, thus making significant strides in the field of breast cancer in the coming decades. By empowering academic investigators, fostering unbiased research, and addressing the limitations of industry-funded IITs, the BCRF-DRC is revolutionizing breast cancer research and driving the development of novel interventions. This abstract highlights the transformative potential of the BCRF-DRC program and its contribution to advancing breast cancer treatments and ultimately improving patient outcomes. The success of this collaborative model serves as a testament to the power of multi-sector partnerships and the pivotal role they play in shaping the future of breast cancer research. Citation Format: Unnati Jariwala, Dorraya El-Ashry, Judy Garber, Larry Norton. The Breast Cancer Research Foundation Drug Research Collaborative – A unique and innovative model for industry-funded, academically driven research to advance the field of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-26-11.

Academia and society should join forces to make anti-cancer treatments more affordable.

Discovery research is the starting point for the development of more effective anti-cancer treatments. It requires an interdisciplinary research environment with first-class infrastructural support in which curiosity-driven research can lead to new concepts for treating cancer. Translating such research findings to clinical practice requires complementary skills and infrastructures, including high-quality clinical facilities, access to patient cohorts and participation of pharma. This complex ecosystem has yielded many new but also "me too" treatment regimens, especially in immuno-oncology resulting in an extremely high pricing of anti-cancer agents. The costs of antibodies, vaccines, and cell therapies charged by pharma stand out although the concepts and methodologies have been largely developed in academia, financed from public funds. Comprehensive Cancer Centres (CCCs) covering a coherent stretch of the cancer research continuum are well-positioned to make these personalized treatments more affordable, but this will require restructuring of the way the translational cancer research continuum is funded.

A Dorsal Skinfold Window Chamber Tumor Mouse Model for Combined Intravital Microscopy and Magnetic Resonance Imaging in Translational Cancer Research.

Preclinical intravital imaging such as microscopy and optical coherence tomography have proven to be valuable tools in cancer research for visualizing the tumor microenvironment and its response to therapy. These imaging modalities have micron-scale resolution but have limited use in the clinic due to their shallow penetration depth into tissue. More clinically applicable imaging modalities such as CT, MRI, and PET have much greater penetration depth but have comparatively lower spatial resolution (mm scale). To translate preclinical intravital imaging findings into the clinic, new methods must be developed to bridge this micro-to-macro resolution gap. Here we describe a dorsal skinfold window chamber tumor mouse model designed to enable preclinical intravital and clinically applicable (CT and MR) imaging in the same animal, and the image analysis platform that links these two disparate visualization methods. Importantly, the described window chamber approach enables the different imaging modalities to be co-registered in 3D using fiducial markers on the window chamber for direct spatial concordance. This model can be used for validation of existing clinical imaging methods, as well as for the development of new ones through direct correlation with "ground truth" high-resolution intravital findings. Finally, the tumor response to various treatments-chemotherapy, radiotherapy, photodynamic therapy-can be monitored longitudinally with this methodology using preclinical and clinically applicable imaging modalities. The dorsal skinfold window chamber tumor mouse model and imaging platforms described here can thus be used in a variety of cancer research studies, for example, in translating preclinical intravital microscopy findings to more clinically applicable imaging modalities such as CT or MRI.

Abstract 3929: Comparative genomics of breast cancer in indigenous African and western populations first results from the E-Predict study

Abstract Breast cancer (BC) stands as the foremost female malignancy globally and is the most prevalent cancer in numerous developing countries, particularly in sub-Saharan Africa (SSA). Over the past decade, significant strides in comprehending the pathobiology of the disease and tumour dynamics have greatly enhanced treatment options, particularly in industrialized nations. Regrettably, SSA countries have witnessed only marginal, if any, improvements, with mortality rates surpassing incidence rates. Unfavourable outcome, early onset and high-grade tumours are predominant in SSA. Despite these challenging clinical phenotypes, there is currently a limited understanding of the primary molecular drivers, primarily due to a dearth of reliable data. Furthermore, there is a paucity of research conducted in, and pertinent to, the challenges of the disease in low-income countries (LICs), despite a rising incidence and higher mortality-to-incidence ratios. We thus established an international translational cancer research consortium in five distinct African countries. This initiative has contributed to the creation of a high-quality repository of biomaterials. Additionally, we have conducted whole exome sequencing on the initial 100 cases of breast cancer, comparing the molecular architecture of these tumors with data from The Cancer Genome Atlas (TCGA). We examining and compared the clinical disease phenotypes between indigenous African women and Western patients. A higher proportion of grade III tumors was observed in African patients aged between 30 to 59 years as compared to other patients within the same age group. In comparative molecular analyses, we found a significantly elevated tumor mutational burden in African patients (median of &amp;gt;15/MB) in contrast to other populations within the TCGA (median ~ 0.7/MB). Gene sets featuring co-occurring mutations, predicted to be associated with survival using the TCGA dataset, showed high mutation rates in the African cohort. Notably, co-occurring mutations between PIK3CA and genes linked to genomic instability, such as BIRC6 (HR: 11.7, p = 2.7e-05), KMT2C (HR: 4.7, p = 4.01e-04), NEB (HR: 3.84, p = 0.48), and PCLO (HR: 4.9, p = 0.016), among others, strongly correlated with poor overall survival and were highly mutated within the African cohort. Interestingly, within the TCGA, patients with early breast cancer onset exhibit twice as many mutations in KMT2C, a gene known for its association with DNA damage repair, genomic instability, and showed an improved response to immune checkpoint inhibition. These initial findings suggest that breast cancer genomics in indigenous African populations may exhibit substantial differences, potentially warranting consideration for distinct therapeutic modalities for these patients. Citation Format: Smiths Sengkwawoh Lueong, Pamela Derliche Tonouo Derliche Tonouo, Arnol Auvaker Tiofack, Rovaldo Nguims Kenfack, Jules Roger Kuiate, Esther Dina Mbassi, Sidonie Noa Ananga, Etienne Okobalemba Atenguena, Gustave Simo, Abdel Jelil Njouendou, Walters Ndaka, Zacharie Sando, Emmanuella Mayemi, Rachel Tayou, Gilles Gael Aghoagni, Anne Sango, Benjamin Pokam, Augustin Tozoula Bambara, Jens T. Siveke. Comparative genomics of breast cancer in indigenous African and western populations first results from the E-Predict study [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 3929.

Abstract 4150: Development of a three-dimensional spatialomics map of lethal prostate cancer driven by clinical imaging

Abstract Prostate adenocarcinoma (PCa) is the most common malignancy and the second leading cause of cancer-related mortality in United States men. Following treatment for localized PCa, up to 50% of these men can experience disease recurrence, with subsequent metastasis and death. This indicates that there is suboptimal identification of lethal PCa at the time of diagnosis, despite advancements in imaging, genomics, and biomarkers. To improve the noninvasive diagnosis of lethal PCa at initial diagnosis, we have developed a novel magnetic resonance imaging (MRI) method, diffusion basis spectrum imaging (DBSI), that noninvasively measures cancer, stromal, and immune cell contributions to the prostate tumor microenvironment (TME). To validate DBSI for PCa, we have applied novel technologies to matched prostatectomy specimens that include (i) fully automated tissue section processing with serial 2-photon tomographic (STP) imaging of the sections to generate 3D volumetric structural maps of the tumor tissue and (ii) multiplex MALDI mass spectrometry imaging of untargeted glycans and extracellular matrix (ECM) peptides and of proteins targeted with novel photocleavable-mass-tagged antibodies (MALDI-IHC) to spatially resolve hundreds of biomolecules from the TME. To establish the feasibility of this approach, we recruited a patient with an unusually aggressive prostate cancer consisting of Gleason 5+4 acinar adenocarcinoma histology with intraductal growth that was locally invasive and lymph node positive at prostatectomy (stage T3bN1). This patient also had the unusual finding of low activity on prostate specific membrane antigen positron emission tomography (PSMA-PET). Following gross sectioning of the prostate with MRI-guided 3D printed molds to co-register clinical DBSI with histology, a 5-mm thick tissue cross-section containing tumor and normal prostate was imaged with high resolution ex vivo DBSI followed by 3D structural mapping with STP imaging. Selected slides in the 3D stack were subject to multiplexed MALDI imaging to identify relationships between cellular and molecular heterogeneity with tumor structure identified with DBSI and STP imaging. We discovered unique structural differences in the prostate tumor compared with the surrounding stroma based upon collagen and glycan modifications to the ECM that were recapitulated with second harmonic maps of collagen from STP imaging as well as stromal maps generated from DBSI imaging. Additional novel protein and glycan ECM components were expressed in this tumor known to be associated with poor patient outcomes. Together, these data represent the first evidence successfully linking noninvasive in vivo clinical imaging and de novo spatialomics technologies with potential to improve PCa diagnostics. This advanced imaging workflow can be applied to any tissue type, underscoring its relevance to translational cancer research. Citation Format: Joseph E. Ippolito, David H. Ballard, Karla Bergeron, Ritesh Chidambaram, Anusha Elumalai, Tyler J. Fraum, Huaping Jing, Peter Kamelin, Eric H. Kim, Catherine Kita, Aleksandra Klim, Anthony Knesis, Mark Lim, José Marcio Luna, Hani Nakhoul, Timothy Ragan, Kenneth J. Rothschild, Sheng-Kwei Song, Kainen Utt, Cody Weimholt, Gargey Yagnik, Elijah Yew, Peggi M. Angel, Richard R. Drake. Development of a three-dimensional spatialomics map of lethal prostate cancer driven by clinical imaging [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 4150.

Abstract 6914: Genomic landscape and stability of preclinical models in NCI's patient-derived models repository

Abstract Background: Patient-derived xenograft (PDX) models serve as a powerful tool for cancer translational research. However, it is unclear to what extent PDX models reflect the genomic intratumoral heterogeneity and genomic aberrations present within the original tumor sample. The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov/) consisting of PDX, organoids (PDOrg), and tumor cell cultures (PDC) from patients with diverse cancer histologies. We have conducted an in-depth investigation into the genomic stability of PDXs at early passaging and tumor heterogeneity in a large set of preclinical models including rare cancers. Methods: Tumor specimens were used to establish 1114 models from 1034 patients. For whole exome sequencing (WES) and RNASeq analysis, 1059 models with at least 1 PDX sample and 55 models with only a PDC or PDOrg were used. Analyzed specimens represent the original patient specimens, PDX passages P0, P1, P2, and P3+ and in vitro models. 80% of the PDX specimens were within passages P0 to P2. Results: Genomic stability in PDMR models was maintained through early passages (P0 - P2) and across independent lineages in PDMR models based on the following observations: 1) variant allele frequencies (VAF) of somatic driver mutations showed no major deviations (exceeding ±10%) when using the stromal fraction corrected VAF from originator data over PDX passages; 2) the median change in the fraction of genome impacted by copy number alterations (CNA) from the originator specimens through passages P0 - P2 was statistically inconsequential, although there was a significant increase in CNA fraction, from 5.3% at P0 initially to 18% by P3; 3) gene expression profiles of specimens within a given PDX model formed clusters in principal component analysis (PCA) plots and showed high correlation (&amp;gt;99.5% models with a Spearman coefficient of &amp;gt;= 0.8). The majority of the PDC and PDOrg specimens exhibited similar findings when compared to the original tumor samples. Furthermore, the positive percent agreement (PPA) was performed to measure the similarity between the patient's tumor and all available derived PDX specimens, with a median PPA over 90%, indicating a high level of retained heterogeneity within the PDX models. Lastly, 69% of models in NCI PDMR had predictive biomarkers, ranging from OncoKB level of evidence 1-4, which could be used to evaluate targeted therapeutics in preclinical studies. Conclusion: The NCI PDMR has a large and histologically diverse cancer representation. In this analysis, the PDXs exhibited genomic stability within early passages and preserved the majority of tumor heterogeneity observed in the patient specimens. NCI PDMR thus represents a valuable resource for researchers interested in preclinical drug screening or other investigations. Citation Format: Ting-Chia Chang, Biswajit Das, Li Chen, Peter I-Fan Wu, Yvonne A. Evrard, Rini Pauly, Dianne L. Newton, Shahanawaz Jiwani, Sergio Y. Alcoser, Luke H. Stockwin, Corinne E. Camalier, Tomas Forbes, Nikitha Nair, Alyssa Chapman, Lindsay Dutko, Michael Mullendore, Tara Grinnage-Pulley, Kimberly Klarmann, Sarah B. Miller, Chris A. Karlovich, Alice P. Chen, P Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Genomic landscape and stability of preclinical models in NCI's patient-derived models repository [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 6914.