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1. Vision Language Models Can Parse Floor Plan Maps

Author

DeFazio, David, Mehta, Hrudayangam, Blackburn, Jeremy, and Zhang, Shiqi

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence
Abstract

Vision language models (VLMs) can simultaneously reason about images and texts to tackle many tasks, from visual question answering to image captioning. This paper focuses on map parsing, a novel task that is unexplored within the VLM context and particularly useful to mobile robots. Map parsing requires understanding not only the labels but also the geometric configurations of a map, i.e., what areas are like and how they are connected. To evaluate the performance of VLMs on map parsing, we prompt VLMs with floorplan maps to generate task plans for complex indoor navigation. Our results demonstrate the remarkable capability of VLMs in map parsing, with a success rate of 0.96 in tasks requiring a sequence of nine navigation actions, e.g., approaching and going through doors. Other than intuitive observations, e.g., VLMs do better in smaller maps and simpler navigation tasks, there was a very interesting observation that its performance drops in large open areas. We provide practical suggestions to address such challenges as validated by our experimental results. Webpage: https://shorturl.at/OUkEY

Published
2024

2. Concurrent RB1 Loss and BRCA Deficiency Predicts Enhanced Immunologic Response and Long-term Survival in Tubo-ovarian High-grade Serous Carcinoma

Author

Saner, Flurina AM, Takahashi, Kazuaki, Budden, Timothy, Pandey, Ahwan, Ariyaratne, Dinuka, Zwimpfer, Tibor A, Meagher, Nicola S, Fereday, Sian, Twomey, Laura, Pishas, Kathleen I, Hoang, Therese, Bolithon, Adelyn, Traficante, Nadia, Group, for the Australian Ovarian Cancer Study, Alsop, Kathryn, Christie, Elizabeth L, Kang, Eun-Young, Nelson, Gregg S, Ghatage, Prafull, Lee, Cheng-Han, Riggan, Marjorie J, Alsop, Jennifer, Beckmann, Matthias W, Boros, Jessica, Brand, Alison H, Brooks-Wilson, Angela, Carney, Michael E, Coulson, Penny, Courtney-Brooks, Madeleine, Cushing-Haugen, Kara L, Cybulski, Cezary, El-Bahrawy, Mona A, Elishaev, Esther, Erber, Ramona, Gayther, Simon A, Gentry-Maharaj, Aleksandra, Gilks, C Blake, Harnett, Paul R, Harris, Holly R, Hartmann, Arndt, Hein, Alexander, Hendley, Joy, Hernandez, Brenda Y, Jakubowska, Anna, Jimenez-Linan, Mercedes, Jones, Michael E, Kaufmann, Scott H, Kennedy, Catherine J, Kluz, Tomasz, Koziak, Jennifer M, Kristjansdottir, Björg, Le, Nhu D, Lener, Marcin, Lester, Jenny, Lubiński, Jan, Mateoiu, Constantina, Orsulic, Sandra, Ruebner, Matthias, Schoemaker, Minouk J, Shah, Mitul, Sharma, Raghwa, Sherman, Mark E, Shvetsov, Yurii B, Soong, T Rinda, Steed, Helen, Sukumvanich, Paniti, Talhouk, Aline, Taylor, Sarah E, Vierkant, Robert A, Wang, Chen, Widschwendter, Martin, Wilkens, Lynne R, Winham, Stacey J, Anglesio, Michael S, Berchuck, Andrew, Brenton, James D, Campbell, Ian, Cook, Linda S, Doherty, Jennifer A, Fasching, Peter A, Fortner, Renée T, Goodman, Marc T, Gronwald, Jacek, Huntsman, David G, Karlan, Beth Y, Kelemen, Linda E, Menon, Usha, Modugno, Francesmary, Pharoah, Paul DP, Schildkraut, Joellen M, Sundfeldt, Karin, Swerdlow, Anthony J, Goode, Ellen L, DeFazio, Anna, Köbel, Martin, Ramus, Susan J, Bowtell, David DL, and Garsed, Dale W

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Immunology, Genetics, Women's Health, Rare Diseases, Orphan Drug, Cancer Genomics, Ovarian Cancer, Precision Medicine, Human Genome, Cancer, 2.1 Biological and endogenous factors, Humans, Female, Ovarian Neoplasms, BRCA2 Protein, BRCA1 Protein, Cystadenocarcinoma, Serous, Retinoblastoma Binding Proteins, Prognosis, Ubiquitin-Protein Ligases, Neoplasm Grading, Lymphocytes, Tumor-Infiltrating, Middle Aged, Germ-Line Mutation, Gene Expression Regulation, Neoplastic, Aged, Biomarkers, Tumor, CD8-Positive T-Lymphocytes, Australian Ovarian Cancer Study Group, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

PurposeThe purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC).Experimental designRB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss.ResultsRB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial-mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.ConclusionsCo-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

Published
2024

3. The Road Less Scheduled

Author

Defazio, Aaron, Yang, Xingyu Alice, Mehta, Harsh, Mishchenko, Konstantin, Khaled, Ahmed, and Cutkosky, Ashok

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Mathematics - Optimization and Control, Statistics - Machine Learning
Abstract

Existing learning rate schedules that do not require specification of the optimization stopping step T are greatly out-performed by learning rate schedules that depend on T. We propose an approach that avoids the need for this stopping time by eschewing the use of schedules entirely, while exhibiting state-of-the-art performance compared to schedules across a wide family of problems ranging from convex problems to large-scale deep learning problems. Our Schedule-Free approach introduces no additional hyper-parameters over standard optimizers with momentum. Our method is a direct consequence of a new theory we develop that unifies scheduling and iterate averaging. An open source implementation of our method is available (https://github.com/facebookresearch/schedule_free).

Published
2024

4. Directional Smoothness and Gradient Methods: Convergence and Adaptivity

Author

Mishkin, Aaron, Khaled, Ahmed, Wang, Yuanhao, Defazio, Aaron, and Gower, Robert M.

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control
Abstract

We develop new sub-optimality bounds for gradient descent (GD) that depend on the conditioning of the objective along the path of optimization, rather than on global, worst-case constants. Key to our proofs is directional smoothness, a measure of gradient variation that we use to develop upper-bounds on the objective. Minimizing these upper-bounds requires solving implicit equations to obtain a sequence of strongly adapted step-sizes; we show that these equations are straightforward to solve for convex quadratics and lead to new guarantees for two classical step-sizes. For general functions, we prove that the Polyak step-size and normalized GD obtain fast, path-dependent rates despite using no knowledge of the directional smoothness. Experiments on logistic regression show our convergence guarantees are tighter than the classical theory based on L-smoothness., Comment: Twenty-four pages

Published
2024

8. Oromandibular dystonia: from onset to spread a multicenter italian study

Author

Trinchillo, Assunta, Esposito, Marcello, Terranova, Carmen, Rizzo, Vincenzo, Fabbrini, Giovanni, Ferrazzano, Gina, Belvisi, Daniele, Erro, Roberto, Barone, Paolo, Bono, Francesco, Di Biasio, Francesca, Bentivoglio, Anna Rita, Lettieri, Christian, Altavista, Maria Concetta, Scaglione, Cesa Lorella Maria, Albanese, Alberto, Mascia, Marcello Mario, Muroni, Antonella, Pisani, Antonio, Berardelli, Alfredo, and Defazio, Giovanni

Published
2024
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9. Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease

Author

Ramachandran, Dhanya, Tyrer, Jonathan P, Kommoss, Stefan, DeFazio, Anna, Riggan, Marjorie J, Webb, Penelope M, Fasching, Peter A, Lambrechts, Diether, García, María J, Rodríguez-Antona, Cristina, Goodman, Marc T, Modugno, Francesmary, Moysich, Kirsten B, Karlan, Beth Y, Lester, Jenny, Kjaer, Susanne K, Jensen, Allan, Høgdall, Estrid, Goode, Ellen L, Cliby, William A, Kumar, Amanika, Wang, Chen, Cunningham, Julie M, Winham, Stacey J, Monteiro, Alvaro N, Schildkraut, Joellen M, Cramer, Daniel W, Terry, Kathryn L, Titus, Linda, Bjorge, Line, Thomsen, Liv Cecilie Vestrheim, Pejovic, Tanja, Høgdall, Claus K, McNeish, Iain A, May, Taymaa, Huntsman, David G, Pfisterer, Jacobus, Canzler, Ulrich, Park-Simon, Tjoung-Won, Schröder, Willibald, Belau, Antje, Hanker, Lars, Harter, Philipp, Sehouli, Jalid, Kimmig, Rainer, de Gregorio, Nikolaus, Schmalfeldt, Barbara, Baumann, Klaus, Hilpert, Felix, Burges, Alexander, Winterhoff, Boris, Schürmann, Peter, Speith, Lisa-Marie, Hillemanns, Peter, Berchuck, Andrew, Johnatty, Sharon E, Ramus, Susan J, Chenevix-Trench, Georgia, Pharoah, Paul DP, Dörk, Thilo, and Heitz, Florian

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Women's Health, Human Genome, Ovarian Cancer, Prevention, Cancer, Orphan Drug, Clinical Research, Rare Diseases, 2.1 Biological and endogenous factors, AOCS Group, OPAL Study Group, Medical biotechnology
Abstract

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10-8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

Published
2024

12. When, Why and How Much? Adaptive Learning Rate Scheduling by Refinement

Author

Defazio, Aaron, Cutkosky, Ashok, Mehta, Harsh, and Mishchenko, Konstantin

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract

Learning rate schedules used in practice bear little resemblance to those recommended by theory. We close much of this theory/practice gap, and as a consequence are able to derive new problem-adaptive learning rate schedules. Our key technical contribution is a refined analysis of learning rate schedules for a wide class of optimization algorithms (including SGD). In contrast to most prior works that study the convergence of the average iterate, we study the last iterate, which is what most people use in practice. When considering only worst-case analysis, our theory predicts that the best choice is the linear decay schedule: a popular choice in practice that sets the stepsize proportionally to $1 - t/T$, where $t$ is the current iteration and $T$ is the total number of steps. To go beyond this worst-case analysis, we use the observed gradient norms to derive schedules refined for any particular task. These refined schedules exhibit learning rate warm-up and rapid learning rate annealing near the end of training. Ours is the first systematic approach to automatically yield both of these properties. We perform the most comprehensive evaluation of learning rate schedules to date, evaluating across 10 diverse deep learning problems, a series of LLMs, and a suite of logistic regression problems. We validate that overall, the linear-decay schedule matches or outperforms all commonly used default schedules including cosine annealing, and that our schedule refinement method gives further improvements.

Published
2023

13. Seeing-Eye Quadruped Navigation with Force Responsive Locomotion Control

Author

DeFazio, David, Hirota, Eisuke, and Zhang, Shiqi

Subjects
Computer Science - Robotics, Computer Science - Machine Learning
Abstract

Seeing-eye robots are very useful tools for guiding visually impaired people, potentially producing a huge societal impact given the low availability and high cost of real guide dogs. Although a few seeing-eye robot systems have already been demonstrated, none considered external tugs from humans, which frequently occur in a real guide dog setting. In this paper, we simultaneously train a locomotion controller that is robust to external tugging forces via Reinforcement Learning (RL), and an external force estimator via supervised learning. The controller ensures stable walking, and the force estimator enables the robot to respond to the external forces from the human. These forces are used to guide the robot to the global goal, which is unknown to the robot, while the robot guides the human around nearby obstacles via a local planner. Experimental results in simulation and on hardware show that our controller is robust to external forces, and our seeing-eye system can accurately detect force direction. We demonstrate our full seeing-eye robot system on a real quadruped robot with a blindfolded human. The video can be seen at our project page: https://bu-air-lab.github.io/guide_dog/, Comment: Accepted to CoRL 2023

Published
2023

14. BRCA1 secondary splice-site mutations drive exon-skipping and PARP inhibitor resistance

Author

Ksenija Nesic, John J. Krais, Yifan Wang, Cassandra J. Vandenberg, Pooja Patel, Kathy Q. Cai, Tanya Kwan, Elizabeth Lieschke, Gwo-Yaw Ho, Holly E. Barker, Justin Bedo, Silvia Casadei, Andrew Farrell, Marc Radke, Kristy Shield-Artin, Jocelyn S. Penington, Franziska Geissler, Elizabeth Kyran, Robert Betsch, Lijun Xu, Fan Zhang, Alexander Dobrovic, Inger Olesen, Rebecca Kristeleit, Amit Oza, Iain McNeish, Gayanie Ratnayake, Nadia Traficante, Australian Ovarian Cancer Study, Anna DeFazio, David D. L. Bowtell, Thomas C. Harding, Kevin Lin, Elizabeth M. Swisher, Olga Kondrashova, Clare L. Scott, Neil Johnson, and Matthew J. Wakefield

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract PARP inhibitor (PARPi) therapy has transformed outcomes for patients with homologous recombination DNA repair (HRR) deficient ovarian cancers, for example those with BRCA1 or BRCA2 gene defects. Unfortunately, PARPi resistance is common. Multiple resistance mechanisms have been described, including secondary mutations that restore the HR gene reading frame. BRCA1 splice isoforms △11 and △11q can contribute to PARPi resistance by splicing out the mutation-containing exon, producing truncated, partially functional proteins. However, the clinical impacts and underlying drivers of BRCA1 exon skipping are not fully understood. We analyzed nine ovarian and breast cancer patient derived xenografts (PDX) with BRCA1 exon 11 frameshift mutations for exon skipping and therapy response, including a matched PDX pair derived from a patient pre- and post-chemotherapy/PARPi. BRCA1 exon 11 skipping was elevated in PARPi resistant PDX tumors. Two independent PDX models acquired secondary BRCA1 splice site mutations (SSMs) that drive exon skipping, confirmed using qRT-PCR, RNA sequencing, immunoblotting and minigene modelling. CRISPR/Cas9-mediated disruption of splicing functionally validated exon skipping as a mechanism of PARPi resistance. SSMs were also enriched in post-PARPi ovarian cancer patient cohorts from the ARIEL2 and ARIEL4 clinical trials. Few PARPi resistance mechanisms have been confirmed in the clinical setting. While secondary/reversion mutations typically restore a gene’s reading frame, we have identified secondary mutations in patient cohorts that hijack splice sites to enhance mutation-containing exon skipping, resulting in the overexpression of BRCA1 hypomorphs, which in turn promote PARPi resistance. Thus, BRCA1 SSMs can and should be clinically monitored, along with frame-restoring secondary mutations.

Published
2024
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16. Prodigy: An Expeditiously Adaptive Parameter-Free Learner

Author

Mishchenko, Konstantin and Defazio, Aaron

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Mathematics - Optimization and Control, Statistics - Machine Learning
Abstract

We consider the problem of estimating the learning rate in adaptive methods, such as AdaGrad and Adam. We propose Prodigy, an algorithm that provably estimates the distance to the solution $D$, which is needed to set the learning rate optimally. At its core, Prodigy is a modification of the D-Adaptation method for learning-rate-free learning. It improves upon the convergence rate of D-Adaptation by a factor of $O(\sqrt{\log(D/d_0)})$, where $d_0$ is the initial estimate of $D$. We test Prodigy on 12 common logistic-regression benchmark datasets, VGG11 and ResNet-50 training on CIFAR10, ViT training on Imagenet, LSTM training on IWSLT14, DLRM training on Criteo dataset, VarNet on Knee MRI dataset, as well as RoBERTa and GPT transformer training on BookWiki. Our experimental results show that our approach consistently outperforms D-Adaptation and reaches test accuracy values close to that of hand-tuned Adam.

Published
2023

17. Mechanic: A Learning Rate Tuner

Author

Cutkosky, Ashok, Defazio, Aaron, and Mehta, Harsh

Subjects
Computer Science - Machine Learning
Abstract

We introduce a technique for tuning the learning rate scale factor of any base optimization algorithm and schedule automatically, which we call \textsc{mechanic}. Our method provides a practical realization of recent theoretical reductions for accomplishing a similar goal in online convex optimization. We rigorously evaluate \textsc{mechanic} on a range of large scale deep learning tasks with varying batch sizes, schedules, and base optimization algorithms. These experiments demonstrate that depending on the problem, \textsc{mechanic} either comes very close to, matches or even improves upon manual tuning of learning rates.

Published
2023

18. MoMo: Momentum Models for Adaptive Learning Rates

Author

Schaipp, Fabian, Ohana, Ruben, Eickenberg, Michael, Defazio, Aaron, and Gower, Robert M.

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control, 90C53, 74S60, 90C06, 62L20, 68W20, 15B52, 65Y20, 68W40, G.1.6
Abstract

Training a modern machine learning architecture on a new task requires extensive learning-rate tuning, which comes at a high computational cost. Here we develop new Polyak-type adaptive learning rates that can be used on top of any momentum method, and require less tuning to perform well. We first develop MoMo, a Momentum Model based adaptive learning rate for SGD-M (stochastic gradient descent with momentum). MoMo uses momentum estimates of the losses and gradients sampled at each iteration to build a model of the loss function. Our model makes use of any known lower bound of the loss function by using truncation, e.g. most losses are lower-bounded by zero. The model is then approximately minimized at each iteration to compute the next step. We show how MoMo can be used in combination with any momentum-based method, and showcase this by developing MoMo-Adam, which is Adam with our new model-based adaptive learning rate. We show that MoMo attains a $\mathcal{O}(1/\sqrt{K})$ convergence rate for convex problems with interpolation, needing knowledge of no problem-specific quantities other than the optimal value. Additionally, for losses with unknown lower bounds, we develop on-the-fly estimates of a lower bound, that are incorporated in our model. We show that MoMo and MoMo-Adam improve over SGD-M and Adam in terms of robustness to hyperparameter tuning for training image classifiers on MNIST, CIFAR, and Imagenet, for recommender systems on Criteo, for a transformer model on the translation task IWSLT14, and for a diffusion model.

Published
2023

19. The Prognostic Effect of Immune Cell Infiltration Depends on Molecular Subtype in Endometrioid Ovarian Carcinomas.

Author

Heinze, Karolin, Cairns, Evan, Thornton, Shelby, Harris, Bronwyn, Milne, Katy, Grube, Marcel, Meyer, Charlotte, Fereday, Sian, Garsed, Dale, Leung, Samuel, Chiu, Derek, Moubarak, Malak, Harter, Philipp, Heitz, Florian, McAlpine, Jessica, DeFazio, Anna, Bowtell, David, Goode, Ellen, Pike, Malcolm, Ramus, Susan, Pearce, C, Staebler, Annette, Köbel, Martin, Kommoss, Stefan, Talhouk, Aline, Nelson, Brad, Anglesio, Michael, and Karnezis, Anthony

Subjects
Female, Humans, Prognosis, Biomarkers, Tumor, Carcinoma, Endometrioid, Ovarian Neoplasms, Endometrial Neoplasms, Carcinoma, Ovarian Epithelial, Tumor Microenvironment
Abstract

PURPOSE: Endometrioid ovarian carcinoma (ENOC) is the second most-common type of ovarian carcinoma, comprising 10%-20% of cases. Recently, the study of ENOC has benefitted from comparisons to endometrial carcinomas including defining ENOC with four prognostic molecular subtypes. Each subtype suggests differential mechanisms of progression, although tumor-initiating events remain elusive. There is evidence that the ovarian microenvironment may be critical to early lesion establishment and progression. However, while immune infiltrates have been well studied in high-grade serous ovarian carcinoma, studies in ENOC are limited. EXPERIMENTAL DESIGN: We report on 210 ENOC, with clinical follow-up and molecular subtype annotation. Using multiplex IHC and immunofluorescence, we examine the prevalence of T-cell lineage, B-cell lineage, macrophages, and populations with programmed cell death protein 1 or programmed death-ligand 1 across subtypes of ENOC. RESULTS: Immune cell infiltrates in tumor epithelium and stroma showed higher densities in ENOC subtypes with known high mutation burden (POLEmut and MMRd). While molecular subtypes were prognostically significant, immune infiltrates were not (overall survival P > 0.2). Analysis by molecular subtype revealed that immune cell density was prognostically significant in only the no specific molecular profile (NSMP) subtype, where immune infiltrates lacking B cells (TILB minus) had inferior outcome (disease-specific survival: HR, 4.0; 95% confidence interval, 1.1-14.7; P < 0.05). Similar to endometrial carcinomas, molecular subtype stratification was generally superior to immune response in predicting outcomes. CONCLUSIONS: Subtype stratification is critical for better understanding of ENOC, in particular the distribution and prognostic significance of immune cell infiltrates. The role of B cells in the immune response within NSMP tumors warrants further study.

Published
2023

20. BRCA1 secondary splice-site mutations drive exon-skipping and PARP inhibitor resistance

Author

Nesic, Ksenija, Krais, John J., Wang, Yifan, Vandenberg, Cassandra J., Patel, Pooja, Cai, Kathy Q., Kwan, Tanya, Lieschke, Elizabeth, Ho, Gwo-Yaw, Barker, Holly E., Bedo, Justin, Casadei, Silvia, Farrell, Andrew, Radke, Marc, Shield-Artin, Kristy, Penington, Jocelyn S., Geissler, Franziska, Kyran, Elizabeth, Betsch, Robert, Xu, Lijun, Zhang, Fan, Dobrovic, Alexander, Olesen, Inger, Kristeleit, Rebecca, Oza, Amit, McNeish, Iain, Ratnayake, Gayanie, Traficante, Nadia, DeFazio, Anna, Bowtell, David D. L., Harding, Thomas C., Lin, Kevin, Swisher, Elizabeth M., Kondrashova, Olga, Scott, Clare L., Johnson, Neil, and Wakefield, Matthew J.

Published
2024
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22. Does thyroid diseases contribute to the natural history of idiopathic adult-onset dystonia? Data from the Italian Dystonia Registry

Author

Idrissi, Sarah, Velucci, Vittorio, Esposito, Marcello, Trinchillo, Assunta, Habestwallner, Francesco, Belvisi, Daniele, Fabbrini, Giovanni, Ferrazzano, Gina, Rizzo, Vincenzo, Terranova, Carmen, Girlanda, Paolo, Pellicciari, Roberta, Avanzino, Laura, Di Biasio, Francesca, Marchese, Roberta, Bono, Francesco, Idone, Giovanni, Laterza, Vincenzo, Lettieri, Christian, Rinaldo, Sara, Eleopra, Roberto, Castagna, Anna, Altavista, Maria Concetta, Moschella, Vincenzo, Erro, Roberto, Barone, Paolo, Barbero, Pierangelo, Ceravolo, Roberto, Mazzucchi, Sonia, Mascia, Marcello Mario, Ercoli, Tommaso, Muroni, Antonella, Zibetti, Maurizio, Lopiano, Leonardo, Scaglione, Cesa Lorella Maria, Bentivoglio, Anna Rita, Petracca, Martina, Magistrelli, Luca, Cotelli, Maria Sofia, Cossu, Giovanni, Squintani, Giovanna Maddalena, De Santis, Tiziana, Schirinzi, Tommaso, Misceo, Salvatore, Pisani, Antonio, Berardelli, Alfredo, and Defazio, Giovanni

Published
2024
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30. Clinical parameters affecting survival outcomes in patients with low-grade serous ovarian carcinoma: an international multicentre analysis

Author

May, Taymaa, Bernardini, Marcus, Lheureux, Stephanie, Aben, Katja KH, Bandera, Elisa V, Beckmann, Matthias W, Benitez, Javier, Berchuck, Andrew, Bjørge, Line, Carney, Michael E, Cramer, Daniel W, deFazio, Anna, Dörk, Thilo, Eccles, Diana M, Friedlander, Michael, García, María Jose, Goode, Ellen L, Hein, Alexander, Høgdall, Claus K, Jensen, Allan, Johnatty, Sharon, Kennedy, Catherine J, Kiemeney, Lambertus A, Kjær, Susanne K, Kupryjańczyk, Jolanta, Matsuo, Keitaro, McGuire, Valerie, Modugno, Francesmary, Paddock, Lisa E, Pejovic, Tanja, Phelan, Catherine M, Riggan, Marjorie J, Rodriguez-Antona, Cristina, Rothstein, Joseph H, Sieh, Weiva, Song, Honglin, Terry, Kathryn L, van Altena, Anne M, Vanderstichele, Adriaan, Vergote, Ignace, Thomsen, Liv Cecilie Vestrheim, Webb, Penelope M, Wentzensen, Nicolas, Wilkens, Lynne R, Ziogas, Argyrios, Jiang, Haiyan, and Tone, Alicia

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Oncology and Carcinogenesis, Ovarian Cancer, Cancer, Clinical Research, Rare Diseases, 6.4 Surgery, Evaluation of treatments and therapeutic interventions, Humans, Female, Middle Aged, Retrospective Studies, Neoplasm Staging, Ovarian Neoplasms, Cystadenocarcinoma, Serous, Kaplan-Meier Estimate, Ovarian Cancer Association and the Australian Ovarian Cancer Study Group, Clinical Sciences, Surgery, Clinical sciences
Abstract

BackgroundWomen with low-grade ovarian serous carcinoma (LGSC) benefit from surgical treatment; however, the role of chemotherapy is controversial. We examined an international database through the Ovarian Cancer Association Consortium to identify factors that affect survival in LGSC.MethodsWe performed a retrospective cohort analysis of patients with LGSC who had had primary surgery and had overall survival data available. We performed univariate and multivariate analyses of progression-free survival and overall survival, and generated Kaplan-Meier survival curves.ResultsOf the 707 patients with LGSC, 680 (96.2%) had available overall survival data. The patients' median age overall was 54 years. Of the 659 patients with International Federation of Obstetrics and Gynecology stage data, 156 (23.7%) had stage I disease, 64 (9.7%) had stage II, 395 (59.9%) had stage III, and 44 (6.7%) had stage IV. Of the 377 patients with surgical data, 200 (53.0%) had no visible residual disease. Of the 361 patients with chemotherapy data, 330 (91.4%) received first-line platinum-based chemotherapy. The median follow-up duration was 5.0 years. The median progression-free survival and overall survival were 43.2 months and 110.4 months, respectively. Multivariate analysis indicated a statistically significant impact of stage and residual disease on progression-free survival and overall survival. Platinum-based chemotherapy was not associated with a survival advantage.ConclusionThis multicentre analysis indicates that complete surgical cytoreduction to no visible residual disease has the most impact on improved survival in LGSC. This finding could immediately inform and change practice.

Published
2023

31. p53 and ovarian carcinoma survival: an Ovarian Tumor Tissue Analysis consortium study

Author

Köbel, Martin, Kang, Eun‐Young, Weir, Ashley, Rambau, Peter F, Lee, Cheng‐Han, Nelson, Gregg S, Ghatage, Prafull, Meagher, Nicola S, Riggan, Marjorie J, Alsop, Jennifer, Anglesio, Michael S, Beckmann, Matthias W, Bisinotto, Christiani, Boisen, Michelle, Boros, Jessica, Brand, Alison H, Brooks‐Wilson, Angela, Carney, Michael E, Coulson, Penny, Courtney‐Brooks, Madeleine, Cushing‐Haugen, Kara L, Cybulski, Cezary, Deen, Suha, El‐Bahrawy, Mona A, Elishaev, Esther, Erber, Ramona, Fereday, Sian, Group, AOCS, Fischer, Anna, Gayther, Simon A, Barquin‐Garcia, Arantzazu, Gentry‐Maharaj, Aleksandra, Gilks, C Blake, Gronwald, Helena, Grube, Marcel, Harnett, Paul R, Harris, Holly R, Hartkopf, Andreas D, Hartmann, Arndt, Hein, Alexander, Hendley, Joy, Hernandez, Brenda Y, Huang, Yajue, Jakubowska, Anna, Jimenez‐Linan, Mercedes, Jones, Michael E, Kennedy, Catherine J, Kluz, Tomasz, Koziak, Jennifer M, Lesnock, Jaime, Lester, Jenny, Lubiński, Jan, Longacre, Teri A, Lycke, Maria, Mateoiu, Constantina, McCauley, Bryan M, McGuire, Valerie, Ney, Britta, Olawaiye, Alexander, Orsulic, Sandra, Osorio, Ana, Paz‐Ares, Luis, Ramón y Cajal, Teresa, Rothstein, Joseph H, Ruebner, Matthias, Schoemaker, Minouk J, Shah, Mitul, Sharma, Raghwa, Sherman, Mark E, Shvetsov, Yurii B, Singh, Naveena, Steed, Helen, Storr, Sarah J, Talhouk, Aline, Traficante, Nadia, Wang, Chen, Whittemore, Alice S, Widschwendter, Martin, Wilkens, Lynne R, Winham, Stacey J, Benitez, Javier, Berchuck, Andrew, Bowtell, David D, dos Reis, Francisco J Candido, Campbell, Ian, Cook, Linda S, DeFazio, Anna, Doherty, Jennifer A, Fasching, Peter A, Fortner, Renée T, García, María J, Goodman, Marc T, Goode, Ellen L, Gronwald, Jacek, Huntsman, David G, Karlan, Beth Y, Kelemen, Linda E, Kommoss, Stefan, Le, Nhu D, and Martin, Stewart G

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer, Rare Diseases, Ovarian Cancer, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Humans, Female, Tumor Suppressor Protein p53, Ovarian Neoplasms, Carcinoma, Ovarian Epithelial, Carcinoma, Endometrioid, ovarian cancer, high-grade serous carcinoma, endometrioid, clear cell, TP53, p53, prognosis, AOCS Group, Clinical sciences
Abstract

Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36-3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11-2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

Published
2023

32. Learning-Rate-Free Learning by D-Adaptation

Author

Defazio, Aaron and Mishchenko, Konstantin

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Mathematics - Optimization and Control, Statistics - Machine Learning
Abstract

D-Adaptation is an approach to automatically setting the learning rate which asymptotically achieves the optimal rate of convergence for minimizing convex Lipschitz functions, with no back-tracking or line searches, and no additional function value or gradient evaluations per step. Our approach is the first hyper-parameter free method for this class without additional multiplicative log factors in the convergence rate. We present extensive experiments for SGD and Adam variants of our method, where the method automatically matches hand-tuned learning rates across more than a dozen diverse machine learning problems, including large-scale vision and language problems. An open-source implementation is available.

Published
2023

34. Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

Author

DeVries, Amber A, Dennis, Joe, Tyrer, Jonathan P, Peng, Pei-Chen, Coetzee, Simon G, Reyes, Alberto L, Plummer, Jasmine T, Davis, Brian D, Chen, Stephanie S, Dezem, Felipe Segato, Aben, Katja KH, Anton-Culver, Hoda, Antonenkova, Natalia N, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Berchuck, Andrew, Bogdanova, Natalia V, Bogdanova-Markov, Nadja, Brenton, James D, Butzow, Ralf, Campbell, Ian, Chang-Claude, Jenny, Chenevix-Trench, Georgia, Cook, Linda S, DeFazio, Anna, Doherty, Jennifer A, Dörk, Thilo, Eccles, Diana M, Eliassen, A Heather, Fasching, Peter A, Fortner, Renée T, Giles, Graham G, Goode, Ellen L, Goodman, Marc T, Gronwald, Jacek, Webb, P, DeFazio, A, Friedlander, M, Obermair, A, Grant, P, Nagle, C, Beesley, V, Chevenix-Trench, G, Bowtell, D, Blomfield, P, Brand, A, Davis, A, Leung, Y, Nicklin, J, Quinn, M, Livingstone, K, O'Neill, H, Williams, M, Black, A, Hadley, A, Glasgow, A, Garrett, A, Rao, A, Shannon, C, Steer, C, Allen, D, Neesham, D, Otton, G, Au-Yeung, G, Goss, G, Wain, G, Gard, G, Robertson, G, Lombard, J, Tan, J, McNeilage, J, Power, J, Coward, J, Miller, J, Carter, J, Lamont, J, Wong, KM, Reid, K, Perrin, L, Milishkin, L, Nascimento, M, Buck, M, Bunting, M, Harrison, M, Chetty, N, Hacker, N, McNally, O, Harnett, P, Beale, P, Awad, R, Mohan, R, Farrell, R, McIntosh, R, Rome, R, Sayer, R, Houghton, R, Hogg, R, Land, R, Baron-Hay, S, and Paramasivum, S

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Human Genome, Cancer, Prevention, Rare Diseases, Ovarian Cancer, Genetic Testing, Aetiology, 2.1 Biological and endogenous factors, Female, Humans, Carcinoma, Ovarian Epithelial, Genome-Wide Association Study, Alleles, DNA Copy Number Variations, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Ovarian Neoplasms, OPAL Study Group, AOCS Group, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P

Published
2022

36. Self-reported awareness of genetic testing, the impact of family history, and access to clinical trials for people diagnosed with ovarian cancer in Australia

Author

Deborah Roczo, Vanessa Alford, Alison Trainer, Anna DeFazio, Amy Pearn, Caitlin Delaney, Megan Cotter, and Sue Hegarty

Subjects
ovarian cancer, genetic testing, patient perspectives, Gynecology and obstetrics, RG1-991, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Objectives: To assess the understanding of people diagnosed with ovarian cancer regarding genetic testing; to understand knowledge gaps among people diagnosed with ovarian cancer that may impact best practice care; and to monitor overall changes in understanding from 2015 to 2022. Design: Longitudinal ’opt-in’ study using an online survey tool at three timepoints: 2015, 2018 and 2022. Participants: People in Australia (or their families / caregivers) diagnosed with ovarian cancer between 2010 and 2022). Main outcome measures: Self-reported awareness of heritable risk factors for ovarian cancer, genetic testing approaches and participation in clinical trials. Results: The study indicated that there have been improvements in the understanding and awareness of people diagnosed with ovarian cancer regarding familial risk (an increase from 43.6% (45 of 149) in 2015 to 62.9% (166 of 264) in 2022); but people were less likely to be aware of the difference between somatic (tumour) and germline testing (120 of 266, 45.1%). However, there were self-reported improvements to clinical trial access in non-metropolitan areas (12 of 64, 18.8% in 2022 compared to 22 of 145, 15.2% in 2018), bringing it on par with metropolitan areas (32 of 169, 18.9% in 2022). Conclusions: Despite improved awareness about genetic testing among people diagnosed with ovarian cancer, there remain knowledge gaps in understanding of genetic testing types (germline and somatic) and gene variant targeted therapies; and further work to improve clinical trial awareness and access is required.

Published
2024
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41. Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease

Author

Dhanya Ramachandran, Jonathan P. Tyrer, Stefan Kommoss, Anna DeFazio, Marjorie J. Riggan, AOCS Group, Penelope M. Webb, Peter A. Fasching, Diether Lambrechts, María J. García, Cristina Rodríguez-Antona, Marc T. Goodman, Francesmary Modugno, Kirsten B. Moysich, Beth Y. Karlan, Jenny Lester, Susanne K. Kjaer, Allan Jensen, Estrid Høgdall, Ellen L. Goode, William A. Cliby, Amanika Kumar, Chen Wang, Julie M. Cunningham, Stacey J. Winham, Alvaro N. Monteiro, Joellen M. Schildkraut, Daniel W. Cramer, Kathryn L. Terry, Linda Titus, Line Bjorge, Liv Cecilie Vestrheim Thomsen, OPAL Study Group, Tanja Pejovic, Claus K. Høgdall, Iain A. McNeish, Taymaa May, David G. Huntsman, Jacobus Pfisterer, Ulrich Canzler, Tjoung-Won Park-Simon, Willibald Schröder, Antje Belau, Lars Hanker, Philipp Harter, Jalid Sehouli, Rainer Kimmig, Nikolaus de Gregorio, Barbara Schmalfeldt, Klaus Baumann, Felix Hilpert, Alexander Burges, Boris Winterhoff, Peter Schürmann, Lisa-Marie Speith, Peter Hillemanns, Andrew Berchuck, Sharon E. Johnatty, Susan J. Ramus, Georgia Chenevix-Trench, Paul D. P. Pharoah, Thilo Dörk, and Florian Heitz

Subjects
Medicine, Genetics, QH426-470
Abstract

Abstract Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10−8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

Published
2024
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43. Grad-GradaGrad? A Non-Monotone Adaptive Stochastic Gradient Method

Author

Defazio, Aaron, Zhou, Baoyu, and Xiao, Lin

Subjects
Computer Science - Machine Learning, Mathematics - Optimization and Control, Statistics - Machine Learning
Abstract

The classical AdaGrad method adapts the learning rate by dividing by the square root of a sum of squared gradients. Because this sum on the denominator is increasing, the method can only decrease step sizes over time, and requires a learning rate scaling hyper-parameter to be carefully tuned. To overcome this restriction, we introduce GradaGrad, a method in the same family that naturally grows or shrinks the learning rate based on a different accumulation in the denominator, one that can both increase and decrease. We show that it obeys a similar convergence rate as AdaGrad and demonstrate its non-monotone adaptation capability with experiments.

Published
2022

44. Increased FOXJ1 protein expression is associated with improved overall survival in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis Consortium Study

Author

Weir, Ashley, Kang, Eun-Young, Meagher, Nicola S, Nelson, Gregg S, Ghatage, Prafull, Lee, Cheng-Han, Riggan, Marjorie J, Gentry-Maharaj, Aleksandra, Ryan, Andy, Singh, Naveena, Widschwendter, Martin, Alsop, Jennifer, Anglesio, Michael S, Beckmann, Matthias W, Berger, Jessica, Bisinotto, Christiani, Boros, Jessica, Brand, Alison H, Brenton, James D, Brooks-Wilson, Angela, Carney, Michael E, Cunningham, Julie M, Cushing-Haugen, Kara L, Cybulski, Cezary, Elishaev, Esther, Erber, Ramona, Fereday, Sian, Fischer, Anna, Paz-Ares, Luis, Gayarre, Javier, Gilks, Blake C, Grube, Marcel, Harnett, Paul R, Harris, Holly R, Hartmann, Arndt, Hein, Alexander, Hendley, Joy, Hernandez, Brenda Y, Heublein, Sabine, Huang, Yajue, Huzarski, Tomasz, Jakubowska, Anna, Jimenez-Linan, Mercedes, Kennedy, Catherine J, Kommoss, Felix KF, Koziak, Jennifer M, Kraemer, Bernhard, Le, Nhu D, Lesnock, Jaime, Lester, Jenny, Lubiński, Jan, Menkiszak, Janusz, Ney, Britta, Olawaiye, Alexander, Orsulic, Sandra, Osorio, Ana, Robles-Díaz, Luis, Ruebner, Matthias, Shah, Mitul, Sharma, Raghwa, Shvetsov, Yurii B, Steed, Helen, Talhouk, Aline, Taylor, Sarah E, Traficante, Nadia, Vierkant, Robert A, Wang, Chen, Wilkens, Lynne R, Winham, Stacey J, Benitez, Javier, Berchuck, Andrew, Bowtell, David D, Candido dos Reis, Francisco J, Cook, Linda S, DeFazio, Anna, Doherty, Jennifer A, Fasching, Peter A, García, María J, Goode, Ellen L, Goodman, Marc T, Gronwald, Jacek, Huntsman, David G, Karlan, Beth Y, Kommoss, Stefan, Modugno, Francesmary, Schildkraut, Joellen M, Sinn, Hans-Peter, Staebler, Annette, Kelemen, Linda E, Ford, Caroline E, Menon, Usha, Pharoah, Paul DP, Köbel, Martin, and Ramus, Susan J

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Ovarian Cancer, Clinical Research, Rare Diseases, Cancer, Aetiology, 2.1 Biological and endogenous factors, Humans, Female, Ovarian Neoplasms, Prognosis, Survival Analysis, RNA, Messenger, Cystadenocarcinoma, Serous, Biomarkers, Tumor, Forkhead Transcription Factors, AOCs group, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundRecently, we showed a >60% difference in 5-year survival for patients with tubo-ovarian high-grade serous carcinoma (HGSC) when stratified by a 101-gene mRNA expression prognostic signature. Given the varied patient outcomes, this study aimed to translate prognostic mRNA markers into protein expression assays by immunohistochemistry and validate their survival association in HGSC.MethodsTwo prognostic genes, FOXJ1 and GMNN, were selected based on high-quality antibodies, correlation with protein expression and variation in immunohistochemical scores in a preliminary cohort (n = 134 and n = 80, respectively). Six thousand four hundred and thirty-four (FOXJ1) and 5470 (GMNN) formalin-fixed, paraffin-embedded ovarian neoplasms (4634 and 4185 HGSC, respectively) represented on tissue microarrays from the Ovarian Tumor Tissue Analysis consortium underwent immunohistochemical staining and scoring, then univariate and multivariate survival analysis.ResultsConsistent with mRNA, FOXJ1 protein expression exhibited a linear, increasing association with improved overall survival in HGSC patients. Women with >50% expression had the most favourable outcomes (HR = 0.78, 95% CI 0.67-0.91, p 35% GMNN expression showed a trend for better outcomes, though this was not significant.ConclusionWe provide foundational evidence for the prognostic value of FOXJ1 in HGSC, validating the prior mRNA-based prognostic association by immunohistochemistry.

Published
2023

45. Lifestyle and personal factors associated with having macroscopic residual disease after ovarian cancer primary cytoreductive surgery

Author

Phung, Minh Tung, Webb, Penelope M, DeFazio, Anna, Fereday, Sian, Lee, Alice W, Bowtell, David DL, Fasching, Peter A, Goode, Ellen L, Goodman, Marc T, Karlan, Beth Y, Lester, Jenny, Matsuo, Keitaro, Modugno, Francesmary, Brenton, James D, Van Gorp, Toon, Pharoah, Paul DP, Schildkraut, Joellen M, McLean, Karen, Meza, Rafael, Mukherjee, Bhramar, Richardson, Jean, Grout, Bronwyn, Chase, Anne, Deurloo, Cindy McKinnon, Terry, Kathryn L, Hanley, Gillian E, Pike, Malcolm C, Berchuck, Andrew, Ramus, Susan J, Pearce, Celeste Leigh, and Consortium, on behalf of the Ovarian Cancer Association

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Estrogen, Rare Diseases, Cancer, Clinical Research, Women's Health, Ovarian Cancer, Contraception/Reproduction, Prevention, 2.1 Biological and endogenous factors, 6.1 Pharmaceuticals, Good Health and Well Being, Pregnancy, Humans, Female, Cytoreduction Surgical Procedures, Retrospective Studies, Ovarian Neoplasms, Carcinoma, Ovarian Epithelial, Parity, Ovarian cancer, Residual disease, Primary cytoreductive surgery, Lifestyle, Ovarian Cancer Association Consortium, Paediatrics and Reproductive Medicine, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis, Reproductive medicine
Abstract

ObjectiveThe presence of macroscopic residual disease after primary cytoreductive surgery (PCS) is an important factor influencing survival for patients with high-grade serous ovarian cancer (HGSC). More research is needed to identify factors associated with having macroscopic residual disease. We analyzed 12 lifestyle and personal exposures known to be related to ovarian cancer risk or inflammation to identify those associated with having residual disease after surgery.MethodsThis analysis used data on 2054 patients with advanced stage HGSC from the Ovarian Cancer Association Consortium. The exposures were body mass index, breastfeeding, oral contraceptive use, depot-medroxyprogesterone acetate use, endometriosis, first-degree family history of ovarian cancer, incomplete pregnancy, menopausal hormone therapy use, menopausal status, parity, smoking, and tubal ligation. Logistic regression models were fit to assess the association between these exposures and having residual disease following PCS.ResultsMenopausal estrogen-only therapy (ET) use was associated with 33% lower odds of having macroscopic residual disease compared to never use (OR = 0.67, 95%CI 0.46-0.97, p = 0.033). Compared to nulliparous women, parous women who did not breastfeed had 36% lower odds of having residual disease (OR = 0.64, 95%CI 0.43-0.94, p = 0.022), while there was no association among parous women who breastfed (OR = 0.90, 95%CI 0.65-1.25, p = 0.53).ConclusionsThe association between ET and having no macroscopic residual disease is plausible given a strong underlying biologic hypothesis between this exposure and diagnosis with HGSC. If this or the parity finding is replicated, these factors could be included in risk stratification models to determine whether HGSC patients should receive PCS or neoadjuvant chemotherapy.

Published
2023

46. Profiling the immune landscape in mucinous ovarian carcinoma.

Author

Meagher, Nicola, Hamilton, Phineas, Milne, Katy, Thornton, Shelby, Harris, Bronwyn, Weir, Ashley, Alsop, Jennifer, Bisinoto, Christiani, Brenton, James, Brooks-Wilson, Angela, Chiu, Derek, Cushing-Haugen, Kara, Fereday, Sian, Garsed, Dale, Gayther, Simon, Gentry-Maharaj, Aleksandra, Gilks, Blake, Jimenez-Linan, Mercedes, Kennedy, Catherine, Le, Nhu, Piskorz, Anna, Riggan, Marjorie, Shah, Mitul, Singh, Naveena, Talhouk, Aline, Widschwendter, Martin, Bowtell, David, Candido Dos Reis, Francisco, Cook, Linda, Fortner, Renée, García, María, Harris, Holly, Huntsman, David, Köbel, Martin, Menon, Usha, Pharoah, Paul, Doherty, Jennifer, Anglesio, Michael, Pike, Malcolm, Pearce, Celeste, Friedlander, Michael, DeFazio, Anna, Nelson, Brad, Ramus, Susan, and Karnezis, Anthony

Subjects
Immune infiltrate, Mucinous ovarian carcinoma, Rare histotype, Humans, Female, B7-H1 Antigen, Carcinoma, Ovarian Epithelial, Ovarian Neoplasms, CD8-Positive T-Lymphocytes, Forkhead Transcription Factors, Lymphocytes, Tumor-Infiltrating, Tumor Microenvironment
Abstract

OBJECTIVE: Mucinous ovarian carcinoma (MOC) is a rare histotype of ovarian cancer, with low response rates to standard chemotherapy, and very poor survival for patients diagnosed at advanced stage. There is a limited understanding of the MOC immune landscape, and consequently whether immune checkpoint inhibitors could be considered for a subset of patients. METHODS: We performed multicolor immunohistochemistry (IHC) and immunofluorescence (IF) on tissue microarrays in a cohort of 126 MOC patients. Cell densities were calculated in the epithelial and stromal components for tumor-associated macrophages (CD68+/PD-L1+, CD68+/PD-L1-), T cells (CD3+/CD8-, CD3+/CD8+), putative T-regulatory cells (Tregs, FOXP3+), B cells (CD20+/CD79A+), plasma cells (CD20-/CD79a+), and PD-L1+ and PD-1+ cells, and compared these values with clinical factors. Univariate and multivariable Cox Proportional Hazards assessed overall survival. Unsupervised k-means clustering identified patient subsets with common patterns of immune cell infiltration. RESULTS: Mean densities of PD1+ cells, PD-L1- macrophages, CD4+ and CD8+ T cells, and FOXP3+ Tregs were higher in the stroma compared to the epithelium. Tumors from advanced (Stage III/IV) MOC had greater epithelial infiltration of PD-L1- macrophages, and fewer PD-L1+ macrophages compared with Stage I/II cancers (p = 0.004 and p = 0.014 respectively). Patients with high epithelial density of FOXP3+ cells, CD8+/FOXP3+ cells, or PD-L1- macrophages, had poorer survival, and high epithelial CD79a + plasma cells conferred better survival, all upon univariate analysis only. Clustering showed that most MOC (86%) had an immune depleted (cold) phenotype, with only a small proportion (11/76,14%) considered immune inflamed (hot) based on T cell and PD-L1 infiltrates. CONCLUSION: In summary, MOCs are mostly immunogenically cold, suggesting they may have limited response to current immunotherapies.

Published
2023

47. Molecular subclasses of clear cell ovarian carcinoma and their impact on disease behavior and outcomes

Author

Bolton, Kelly L, Chen, Denise, de la Fuente, Rosario I Corona, Fu, Zhuxuan, Murali, Rajmohan, K�bel, Martin, Tazi, Yanis, Cunningham, Julie M, Chan, Irenaeus CC, Wiley, Brian J, Moukarzel, Lea A, Winham, Stacey J, Armasu, Sebastian M, Lester, Jenny, Elishaev, Esther, Laslavic, Angela, Kennedy, Catherine J, Piskorz, Anna, Sekowska, Magdalena, Brand, Alison H, Chiew, Yoke-Eng, Pharoah, Paul, Elias, Kevin M, Drapkin, Ronny, Churchman, Michael, Gourley, Charlie, DeFazio, Anna, Karlan, Beth, Brenton, James D, Weigelt, Britta, Anglesio, Michael S, Huntsman, David, Gayther, Simon A, Konner, Jason, Modugno, Francesmary, Lawrenson, Kate, Goode, Ellen L, and Papaemmanuil, Elli

Subjects
Rare Diseases, Ovarian Cancer, Genetics, Cancer, Clinical Research, Good Health and Well Being, Female, Humans, Ovarian Neoplasms, Adenocarcinoma, Clear Cell, Mutation, Endometriosis, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

PurposeTo identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes.Experimental designWe profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival.ResultsWe detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy.ConclusionsOur study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

Published
2022

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