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The Salento Prognostic Model For Limited-Stage Peripheral T-Cell Lymphoma From The International T-Cell Project Network, Greg Hapgood, Monica Civallero, Yana Stepanishyna, Julie M. Vose, Monica Elena Cabrera, Ranjana H Advani, Stefano A. Pileri, Martina Manni, Steven M. Horwitz, Francine M. Foss, Felicitas Hitz, John Radford, Ivan Dlouhy, Carlos Chiattone, Won Seog Kim, Tetiana Skrypets, Arnon Nagler, Judith Trotman, Stefano Luminari, Massimo Federico

Journal Articles: Oncology and Hematology

The natural history of limited-stage peripheral T-cell lymphomas (PTCLs) remains poorly defined. We investigated outcomes and prognostic variables in patients registered in the T-Cell Project (TCP) (#NCT01142674) to develop a model to predict overall survival (OS) for the common nodal PTCL subtypes (PTCL-NOS, AITL, ALCL). The model was validated in an independent data set from Australian and Brazilian registries. 211 patients registered in the TCP between 2006-2018 were studied. The median age was 59 years (range 18-88) and median follow-up was 49 months. One hundred twenty-seven patients (78%) received anthracycline-based regimens, 5 patients (3%) radiotherapy alone (RT), 24 patients (15%) …

High-Grade B-Cell Lymphoma, Not Otherwise Specified: A Multi-Institutional Retrospective Study, Adam S. Zayac, Daniel J. Landsburg, Mitchell E. Hughes, Allison M. Bock, Grzegorz S. Nowakowski, Emily C. Ayers, Mark Girton, Marie Hu, Amy K. Beckman, Shaoying Li, L Jeffrey Medeiros, Julie E. Chang, Adam Stepanovic, Habibe Kurt, Jose Sandoval-Sus, M Ali Ansari-Lari, Shalin K. Kothari, Anna Kress, Mina L. Xu, Pallawi Torka, Suchitra Sundaram, Stephen D. Smith, Kikkeri N. Naresh, Yasmin H. Karimi, Narendranath Epperla, David A. Bond, Umar Farooq, Mahak Saad, Andrew M. Evens, Karan Pandya, Seema G. Naik, Manali Kamdar, Bradley Haverkos, Reem Karmali, Timothy S. Oh, Julie M. Vose, Heather Nutsch, Paul G. Rubinstein, Amina Chaudhry, Adam J. Olszewski

Journal Articles: Oncology and Hematology

In this multi-institutional retrospective study, we examined the characteristics and outcomes of 160 patients with high-grade B-cell lymphoma, not otherwise specified (HGBL-NOS)-a rare category defined by high-grade morphologic features and lack of MYC rearrangements with BCL2 and/or BCL6 rearrangements ("double hit"). Our results show that HGBL-NOS tumors are heterogeneous: 83% of patients had a germinal center B-cell immunophenotype, 37% a dual-expressor immunophenotype (MYC and BCL2 expression), 28% MYC rearrangement, 13% BCL2 rearrangement, and 11% BCL6 rearrangement. Most patients presented with stage IV disease, a high serum lactate dehydrogenase, and other high-risk clinical factors. Most frequent first-line regimens included dose-adjusted cyclophosphamide, …

Machine Learning Analyses Of Highly-Multiplexed Immunofluorescence Identifies Distinct Tumor And Stromal Cell Populations In Primary Pancreatic Tumors, Krysten Vance, Alphan Alitinok, Seth Winfree, Heather Jensen Smith, Benjamin Swanson Md, Phd, Paul M. Grandgenett, Kelsey Klute, Daniel J Crichton, Michael A. Hollingsworth

Journal Articles: Eppley Institute

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge for patients and clinicians.

OBJECTIVE: To analyze the distribution of 31 different markers in tumor and stromal portions of the tumor microenvironment (TME) and identify immune cell populations to better understand how neoplastic, non-malignant structural, and immune cells, diversify the TME and influence PDAC progression.

METHODS: Whole slide imaging (WSI) and cyclic multiplexed-immunofluorescence (MxIF) was used to collect 31 different markers over the course of nine distinctive imaging series of human PDAC samples. Image registration and machine learning algorithms were developed to largely automate an imaging analysis pipeline identifying distinct cell …

Human Islet Response To Selected Type 1 Diabetes-Associated Bacteria: A Transcriptome-Based Study, Ahmed M. Abdellatif, Heather Jensen Smith, Robert Z. Harms, Nora Sarvetnick

Journal Articles: Eppley Institute

Type 1 diabetes (T1D) is a chronic autoimmune disease that results from destruction of pancreatic β-cells. T1D subjects were recently shown to harbor distinct intestinal microbiome profiles. Based on these findings, the role of gut bacteria in T1D is being intensively investigated. The mechanism connecting intestinal microbial homeostasis with the development of T1D is unknown. Specific gut bacteria such as Bacteroides dorei (BD) and Ruminococcus gnavus (RG) show markedly increased abundance prior to the development of autoimmunity. One hypothesis is that these bacteria might traverse the damaged gut barrier, and their constituents elicit a response from human islets that causes …

The Distinct Metabolic Phenotype Of Lung Squamous Cell Carcinoma Defines Selective Vulnerability To Glycolytic Inhibition, Justin Goodwin, Michael L. Neugent, Shin Yup Lee, Joshua H. Choe, Hyunsung Choi, Dana M. R. Jenkins, Robin J. Ruthenborg, Maddox W. Robinson, Ji Yun Jeong, Masaki Wake, Hajime Abe, Norihiko Takeda, Hiroko Endo, Masahiro Inoue, Zhenyu Xuan, Hyuntae Yoo, Min Chen, Jung-Mo Ahn, John D. Minna, Kristi L. Helke, Pankaj K. Singh, David B. Shackelford, Jung-Whan Kim

Journal Articles: Eppley Institute

Adenocarcinoma (ADC) and squamous cell carcinoma (SqCC) are the two predominant subtypes of non-small cell lung cancer (NSCLC) and are distinct in their histological, molecular and clinical presentation. However, metabolic signatures specific to individual NSCLC subtypes remain unknown. Here, we perform an integrative analysis of human NSCLC tumour samples, patient-derived xenografts, murine model of NSCLC, NSCLC cell lines and The Cancer Genome Atlas (TCGA) and reveal a markedly elevated expression of the GLUT1 glucose transporter in lung SqCC, which augments glucose uptake and glycolytic flux. We show that a critical reliance on glycolysis renders lung SqCC vulnerable to glycolytic inhibition, …

Invariant Characteristics Of Carcinogenesis., Simon Sherman, Nirosha Rathnayake, Tengiz Mdzinarishvili

Journal Articles: Eppley Institute

Carcinogenic modeling is aimed at mathematical descriptions of cancer development in aging. In this work, we assumed that a small fraction of individuals in the population is susceptible to cancer, while the rest of the population is resistant to cancer. For individuals susceptible to cancer we adopted methods of conditional survival analyses. We performed computational experiments using data on pancreatic, stomach, gallbladder, colon and rectum, liver, and esophagus cancers from the gastrointestinal system collected for men and women in the SEER registries during 1975-2009. In these experiments, we estimated the time period effects, the birth cohort effects, the age effects …

Targeted Mutational Profiling Of Peripheral T-Cell Lymphoma Not Otherwise Specified Highlights New Mechanisms In A Heterogeneous Pathogenesis., J. H. Schatz, S. M. Horwitz, J. Teruya-Feldstein, Matthew A. Lunning, A. Viale, K. Huberman, N. D. Socci, N. Lailler, A. Heguy, I. Dolgalev, J. C. Migliacci, M. Pirun, M. L. Palomba, D. M. Weinstock, H-G Wendel

Journal Articles: Oncology and Hematology

No abstract provided.

Heuristic Modeling Of Carcinogenesis For The Population With Dichotomous Susceptibility To Cancer: A Pancreatic Cancer Example., Tengiz Mdzinarishvili, Simon Sherman

Journal Articles: Eppley Institute

At present, carcinogenic models imply that all individuals in a population are susceptible to cancer. These models either ignore a fall of the cancer incidence rate at old ages, or use some poorly identifiable parameters for its accounting. In this work, a new heuristic model is proposed. The model assumes that, in a population, only a small fraction (pool) of individuals is susceptible to cancer and decomposes the problem of the carcinogenic modeling on two sequentially solvable problems: (i) determination of the age-specific hazard rate in individuals susceptible to cancer (individual hazard rate) from the observed hazard rate in the …

A Heuristic Solution Of The Identifiability Problem Of The Age-Period-Cohort Analysis Of Cancer Occurrence: Lung Cancer Example., Tengiz Mdzinarishvili, Simon Sherman

Journal Articles: Eppley Institute

BACKGROUND: The Age-Period-Cohort (APC) analysis is aimed at estimating the following effects on disease incidence: (i) the age of the subject at the time of disease diagnosis; (ii) the time period, when the disease occurred; and (iii) the date of birth of the subject. These effects can help in evaluating the biological events leading to the disease, in estimating the influence of distinct risk factors on disease occurrence, and in the development of new strategies for disease prevention and treatment.

METHODOLOGY/PRINCIPAL FINDINGS: We developed a novel approach for estimating the APC effects on disease incidence rates in the frame of …