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Rxivist combines biology preprints from bioRxiv and medRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 172,981 papers from 714,387 authors.

Most downloaded biology preprints, since beginning of last month

in category oncology

638 results found. For more information, click each entry to expand.

1: Complete remission in a patient with widely metastatic HER2-amplified pancreatic adenocarcinoma following multimodal therapy informed by tumor sequencing and organoid profiling
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Posted 21 Dec 2021

Complete remission in a patient with widely metastatic HER2-amplified pancreatic adenocarcinoma following multimodal therapy informed by tumor sequencing and organoid profiling
500 downloads medRxiv oncology

Daniel A King, Amber R Smith, Gino Pineda, Michitaka Nakano, Flavia Michelini, S. Peter Goedegebuure, Sheeno Thyparambil, Aaron McCormick, Jihang Ju, Michele Cioffi, Malachi Griffith, Carla Grandori, Maddy Pollastro, Rachele Rosati, Astrid Margossian, Payel Chatterjee, Trevor Ainge, Marta Flory, Paolo Ocampo, Lee-may Chen, George A Poultsides, Ari D Baron, Daniel T. Chang, Joseph M Herman, William E Gillanders, Haeseong Park, William A Hoos, Mike Nichols, George A Fisher, Calvin J Kuo

This work, "Complete remission in a patient with widely metastatic HER2-amplified pancreatic adenocarcinoma following multimodal therapy informed by tumor sequencing and organoid profiling" highlights the power of multi-institution collaboration, combining strengths in organoid profiling (Kuo group at Stanford), personalized vaccine therapy (Gillanders group at WUSTL), in vitro drug testing and drug sensitivity (SEngine, MSK, and Mprobe), clinical trials (Dr Ari Baron at CPMC), and the Canopy Health learning network. Here, we demonstrate a complete clinical response achieved in a patient with HER2+ metastatic pancreatic ductal adenocarcinoma to a coordinated barrage of anti-HER2, personalized vaccine and checkpoint inhibition immunotherapy, radiation, and chemotherapy. Comprehensive organoid profiling with drug sensitivity screening and drug testing suggested a vulnerability to anti-HER2 directed therapy, facilitating personalized treatment selection for our patient, which contributed to her clinical benefit. Immune response monitoring following personalized vaccine, radiation and checkpoint inhibition showed a sustained increase in neoantigen specific T cell response.

2: Single-cell physical phenotyping of mechanically dissociated tissue biopsies for fast diagnostic assessment
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Posted 02 Dec 2021

Single-cell physical phenotyping of mechanically dissociated tissue biopsies for fast diagnostic assessment
309 downloads medRxiv oncology

Despina Soteriou, Markéta Kubánková, Christine Schweitzer, Rocío López-Posadas, Rashmita Pradhan, Oana-Maria Thoma, Andrea-Hermina Györfi, Alexandru-Emil Matei, Maximilian Waldner, Jörg H.W. Distler, Stefan Scheuermann, Jens Langejürgen, Regine Schneider-Stock, Raja Atreya, Markus F. Neurath, Arndt Hartmann, Jochen Guck

Rapid and accurate histopathological diagnosis during surgery is critical for clinical decision-making. The prevalent method of intraoperative consultation pathology is time, labour and cost intensive and requires the expertise of trained pathologists. Here, we present an alternative technique for the rapid, label-free analysis of biopsy samples by sequentially assessing the physical phenotype of singularized, suspended cells in high-throughput. This new diagnostic pipeline combines enzyme-free, mechanical dissociation of tissues with real-time deformability cytometry at measurement rates of 100 - 1,000 cells/sec, and machine learning-based analysis. We show that physical phenotype parameters extracted from brightfield images of single cells can be used to distinguish subpopulations of cells in various tissues, without prior knowledge or the need for molecular markers. Further, we demonstrate the potential of our method for inflammatory bowel disease diagnostics. Using unsupervised dimensionality reduction and logistic regression, we accurately differentiate between healthy and tumorous tissue in both mouse and human biopsy samples. The method delivers results within 30 minutes, laying the groundwork for a fast and marker-free diagnostic pipeline to detect pathological changes in solid biopsies.

3: A comprehensive systematic review and meta-analysis of the global data involving 61,532 cancer patients with SARS-CoV-2 infection.
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Posted 19 Dec 2021

A comprehensive systematic review and meta-analysis of the global data involving 61,532 cancer patients with SARS-CoV-2 infection.
211 downloads medRxiv oncology

Emma Khoury, Sarah Nevitt, William Rohde Madsen, Lance Turtle, Gerry Davies, Carlo Palmieri

Abstract Background SARS-CoV-2 have been shown to be associated with more severe disease and death in cancer patient. A systematic review and meta-analysis was conducted to determine the risk by age, tumour type and treatment of infection with SARS-CoV-2 in cancer patients. Methods Systematic review by searching PubMed, Web of Science, and Scopus for articles published in English up to June 14, 2021 of SARS-CoV-2 infection in >10 patients with malignant disease. Outcomes included factors in patients with malignant disease that may predict a poor outcome from COVID-19 compared to patients without malignant disease, including patient demographics, tumour subtype and cancer treatments. A meta-analysis was performed using random effects model. Results 81 studies were included, totalling 61,532 cancer patients. Haematological malignancies comprised 22.1% (9,672 of 43,676) of cases. Relative risk (RR) of mortality when age and sex matched was 1.69 (95% CI, 1.46-1.95; p<0.001; I2=51%). RR of mortality, versus non-cancer patients, was associated with decreasing age (exp(b)0.96; 95% CI, 0.922-0.994; p=0.028) but not male sex (exp(b)1.89; 95% CI, 0.222-6.366; p=0.83). RR of mortality in those with haematological malignancies versus non-cancer control was 1.81 (95% CI, 1.53-2.95; I2=0.0%). Compared to other cancers, increased risk of death was seen for lung (RR 1.68, 95% CI, 1.45-1.94; p<0.001), genitourinary (RR 1.11; 95% CI, 1.00-1.24; p=0.059) and haematological malignancies (RR 1.42; 95% CI, 1.31-1.54; p<0.001). Breast (RR 0.51; 95% CI, 0.36-0.71; p<0.001) and gynaecological cancers (RR 0.76; 95% CI, 0.62-0.93; p=0.009) had lower risk of death. Receipt of chemotherapy had greatest overall pooled mortality risk of 30% (95% CI, 25-36%; I2=86.97%) and endocrine therapy the lowest at 11% (95% CI, 6-16%; I2=70.7%). Conclusions Cancer patients, particularly younger cancer patients, appear at increased risk of mortality from COVID-19 compared to non-cancer patients. Differences in outcomes were seen based on tumour types and treatment.

4: Cytokine release syndrome-like serum responses after COVID-19 vaccination are frequent but clinically inapparent in cancer patients under immune checkpoint therapy
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Posted 11 Dec 2021

Cytokine release syndrome-like serum responses after COVID-19 vaccination are frequent but clinically inapparent in cancer patients under immune checkpoint therapy
174 downloads medRxiv oncology

Thomas Walle, Sunanjay Bajaj, Joscha A Kraske, Thomas Roesner, Christiane Sophie Cussigh, Katharina Anna Kaelber, Lisa Jasmin Mueller, Sophia Boyoung Strobel, Jana Burghaus, Stefan Kallenberger, Christoph Stein-Thoeringer, Maximilian Jenzer, Antonia Schubert, Steffen Kahle, Anja Williams, Birgit Hoyler, Lin Zielske, Renate Skatula, Stefanie Sawall, Mathias Felix Leber, Russell Z Kunes, Johannes Krisam, Carlo Fremd, Andreas Schneeweiss, Juergen Krauss, Anne Katrin Berger, Georg Martin Haag, Stefanie Zschaebitz, Niels Halama, Christoph Springfeld, Romy Kirsten, Jessica C Hassel, Dirk Jaeger, NCT ANTICIPATE Investigators, Guy Ungerechts

Cancer patients frequently receive immune checkpoint therapies (ICT) which may modulate immune responses to COVID-19 vaccines. Recently, a cytokine release syndrome (CRS) was observed in a cancer patient who received the BTN162b2 vaccine under ICT. Here, we analyzed adverse events (AEs) in patients of various solid tumor types undergoing (n=64) or not undergoing (n=26) COVID-19 vaccination under ICT as an exploratory endpoint of a prospectively planned cohort study. We did not observe clinically relevant CRS after vaccination (95% CI [0,0.056]). Short term (<4 weeks) serious AEs were rare (12.5%) and overall AEs under ICT were comparable to unvaccinated patients. Despite the absence of CRS symptoms, we observed a pairwise-correlated set of CRS-associated cytokines upregulated in 42% of patients after vaccination and ICT (>1.5fold). Hence, clinically meaningful CRS appears to be rare in cancer patients under ICT and elevated serum cytokine levels are common but not sufficient to establish CRS diagnosis.

5: Genetic Subgroups Inform on Pathobiology in Adult and Pediatric Burkitt Lymphoma
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Posted 08 Dec 2021

Genetic Subgroups Inform on Pathobiology in Adult and Pediatric Burkitt Lymphoma
173 downloads medRxiv oncology

Nicole Thomas, Kostiantyn Dreval, Daniela S. Gerhard, Laura K Hilton, Jeremy S Abramson, Nancy L Bartlett, Jeffrey Bethony, Jay Bowen, Anthony C. Bryan, Corey Casper, Manuela Cruz, Maureen A Dyer, Pedro Farinha, Julie M Gastier-Foster, Alina S Gerrie, Bruno M. Grande, Timothy Greiner, Nicholas B Griner, Thomas G Gross, Nancy L Harris, John D Irvin, Elaine S. Jaffe, Fabio E. Leal, Jean Paul Martin, Marie-Reine Martin, Sam M Mbulaiteye, Charles Mullighan, Andrew J Mungall, Karen Mungall, Constance Namirembe, Ariela Noy, Martin D Ogwang, Jackson Orem, German Ott, Hilary Petrello, Steven J Reynolds, Graham Slack, Shaghayegh Soudi, Steven H Swerdlow, Alexandra Traverse-Glehen, Wyndham H Wilson, Jasper Wong, Marco A Marra, Louis M. Staudt, David W Scott, Ryan D Morin

Burkitt lymphoma (BL) accounts for the majority of pediatric non-Hodgkin lymphomas (NHL) and is relatively rare but significantly more lethal when diagnosed in adults. The global incidence is highest in Sub-Saharan Africa, where Epstein-Barr virus (EBV) positivity is observed in 95% of all tumors. Both pediatric (pBL) and adult (aBL) cases are known to share some driver mutations, for example MYC translocations, which are seen in > 90% of cases. Sequencing efforts have identified many common somatic alterations that cooperate with MYC in lymphomagenesis with approximately 30 significantly mutated genes (SMG) reported thus far. Recent analyses revealed non-coding mutation patterns in pBL that were attributed to aberrant somatic hypermutation (aSHM). We sought to identify genomic and molecular features that may explain clinical disparities within and between aBL and pBL in an effort to delineate BL subtypes that may allow for the stratification of patients with shared pathobiology. Through comprehensive sequencing of BL genomes, we found additional SMGs, including more genetic features that associate with tumor EBV status, and established three new genetic subgroups that span pBL and aBL. Direct comparisons between pBL and aBL revealed only marginal differences and the mutational profiles were consistently better explained by EBV status. Using an unsupervised clustering approach to identify subgroupings within BL and diffuse large B-cell lymphoma (DLBCL), we have defined three genetic subgroups that predominantly comprise BL tumors. Akin to the recently defined DLBCL subgroups, each BL subgroup is characterized by combinations of common driver mutations and non-coding mutations caused by aSHM. Two of these subgroups and their prototypical genetic features (ID3 and TP53) had significant associations with patient outcomes that were different among the aBL and pBL cohorts. These findings highlight not only a shared pathogenesis between aBL and pBL, but also establish genetic subtypes within BL that serve to delineate tumors with distinct molecular features, providing a new framework for epidemiological studies, and diagnostic and therapeutic strategies.

6: Validation of Genomic and Transcriptomic Models of Homologous Recombination Deficiency in a Real-World Pan-Cancer Cohort
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Posted 21 Dec 2021

Validation of Genomic and Transcriptomic Models of Homologous Recombination Deficiency in a Real-World Pan-Cancer Cohort
170 downloads medRxiv oncology

Benjamin D. Leibowitz, Bonnie V Dougherty, Joshua S.K. Bell, Joshuah Kapilivsky, Jackson Michuda, Andrew J Sedgewick, Wesley A Munson, Tushar A Chandra, Jonathan R Dry, Nike Beaubier, Catherine Igartua, Timothy Taxter

Background: With the introduction of DNA-damaging therapies into standard of care cancer treatment, there is a growing need for predictive diagnostics assessing homologous recombination deficiency (HRD) status across tumor types. Following the strong clinical evidence for the utility of DNA-sequencing-based HRD testing in ovarian cancer, and growing evidence in breast cancer, we present analytical validation of the Tempus|HRD-DNA test. We further developed, validated, and explored the Tempus|HRD-RNA model, which uses gene expression data from 16,470 RNA-seq samples to predict HRD status from formalin-fixed paraffin-embedded (FFPE) tumor samples across numerous cancer types. Methods: Genomic and transcriptomic profiling was performed using next-generation sequencing from Tempus|xT, Tempus|xO, Tempus|xE, Tempus|RS, and Tempus|RS.v2 assays on 48,843 samples. Samples were labeled based on their BRCA1, BRCA2 and selected Homologous Recombination Repair (HRR) pathway gene (CDK12, PALB2, RAD51B, RAD51C, RAD51D) mutational status to train and validate HRD-DNA, a genome-wide loss-of-heterozygosity biomarker, and HRD-RNA, a logistic regression model trained on gene expression, using several performance metrics and statistical tests. Results: In a sample of 2,058 breast and 1,216 ovarian tumors, BRCA status was predicted by HRD-DNA with F1-scores of 0.98 and 0.96, respectively. Across an independent set of 1,363 samples across solid tumor types, the HRD-RNA model was predictive of BRCA status in prostate, pancreatic, and non-small cell lung cancer, with F1-scores of 0.88, 0.69, and 0.62, respectively. Conclusions: We predict HRD-positive patients across many cancer types and believe both HRD models may generalize to other mechanisms of HRD outside of BRCA loss. HRD-RNA complements DNA-based HRD detection methods, especially for indications with low prevalence of BRCA alterations.

7: Treatment of Recurrent Glioblastoma by Chronic Convection-Enhanced Delivery of Topotecan
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Posted 06 Dec 2021

Treatment of Recurrent Glioblastoma by Chronic Convection-Enhanced Delivery of Topotecan
150 downloads medRxiv oncology

Eleonora F Spinazzi, Michael G Argenziano, Pavan S Upadhyayula, Matei A Banu, Justin A Neira, Dominique M O Higgins, Peter B Wu, Brianna Pereira, Aayushi Mahajan, Nelson Humala, Osama Al-Dalahmah, Wenting Zhao, Akshay V Save, Deborah M. Boyett, Tamara Marie, Julia L Furnari, Tejaswi D. Sudhakar, Sylwia A. Stopka, Michael Regan, Vanessa Catania, Laura Good, Meenu Behl, Sachin Jambawalikar, Akiva Mintz, Angela Lignelli, Nathalie YR Agar, Peter A. Sims, Mary Welch, Andrew Lassman, Fabio Iwamoto, Randy S D'Amico, Jack Grinband, Peter Canoll, Jeffrey N Bruce

Glioblastoma, the most common primary brain malignancy, is invariably fatal. Systemic chemotherapy is ineffective mostly because of drug delivery limitations. To overcome this, we devised an internalized pump-catheter system for direct chronic convection-enhanced delivery (CED) into peritumoral brain tissue. Topotecan (TPT) by chronic CED in 5 patients with refractory glioblastoma selectively eliminated tumor cells without toxicity to normal brain. Large, stable drug distribution volumes were non-invasively monitored with MRI of co-infused gadolinium. Analysis of multiple radiographically localized biopsies taken before and after treatment showed a decreased proliferative tumor signature resulting in a shift to a slow-cycling mesenchymal/astrocytic-like population. Tumor microenvironment analysis showed an inflammatory response and preservation of neurons. This novel drug delivery strategy and innovative clinical trial paradigm overcomes current limitations in delivery and treatment response assessment as shown here for glioblastoma and is potentially applicable for other anti-glioma agents as well as other CNS diseases.

8: RNA Sequencing-Based Single Sample Predictors of Molecular Subtype and Risk of Recurrence for Clinical Assessment of Early-Stage Breast Cancer
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Posted 05 Dec 2021

RNA Sequencing-Based Single Sample Predictors of Molecular Subtype and Risk of Recurrence for Clinical Assessment of Early-Stage Breast Cancer
143 downloads medRxiv oncology

Johan Staaf, Jari Häkkinen, Cecilia Hegardt, Lao H Saal, Siker Kimbung, Ingrid Hedenfalk, Tonje Lien, Therese Sørlie, Bjørn Naume, Hege Russnes, Rachel Marcone, Ayyakkannu Ayyanan, Cathrin Brisken, Rebecka R Malterling, Bengt Asking, Helena Olofsson, Henrik Lindman, Pär-Ola Bendahl, Anna Ehinger, Christer Larsson, Niklas Loman, Lisa Rydén, Martin Malmberg, Åke Borg, Johan Vallon-Christersson

BackgroundMultigene expression assays for molecular subtypes and biomarkers can aid clinical management of early breast cancer. Based on RNA-sequencing we aimed to develop robust single-sample predictor (SSP) models for conventional clinical markers as well as molecular intrinsic subtype and risk of recurrence (ROR) that provide clinically relevant prognostic stratification. MethodsA uniformly accrued breast cancer cohort of 7743 patients with RNA-sequencing data from fresh tissue was divided into a training set (n=5250) and a reserved test set (n=2412). We trained SSPs for PAM50 molecular subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for conventional clinical markers from histopathology data. Additionally, SSP classifications were compared with Prosigna in two external clinical series (ABiM, n=100 and OSLO2-EMIT0, n=103 cases). ResultsIn the test set, agreement between SSP and NC classifications for PAM50 (five subtypes) and Subtype (four subtypes) was high (85%, Kappa=0.78) and very high (90%, Kappa=0.84) respectively. Accuracy for ROR risk category was high (84%, Kappa=0.75, weighted Kappa=0.90). The prognostic value for SSP and NC classification was assessed as equivalent and added clinically relevant prognostic information. Agreement for SSP and histopathology was very high or high for receptor status, while moderate and poor for Ki67 status and Nottingham histological grade (NHG), respectively. SSP concordance with Prosigna was high for subtype (OSLO=83% and ABiM=80%, Kappa=0.73 and 0.72, respectively) and moderate and high for ROR risk category (68% and 84%, Kappa=0.50 and 0.70, weighted Kappa=0.70 and 0.78). In pooled analysis, concordance between SSP and Prosigna for emulated treatment recommendation dichotomized for chemotherapy (yes vs. no) was high (85%, Kappa=0.66). In postmenopausal ER+/ HER2-/N0 patients SSP application suggested changed treatment recommendations for up to 17% of patients, with nearly balanced escalation and de-escalation of therapy. ConclusionsRobust SSP models, mimicking histopathological variables, PAM50, and ROR classifications can be derived from RNA-sequencing that closely matches clinical tests. Agreement and outcome analyses suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level. Retrospective evaluation in ER+/HER2-/ N0 early breast cancer suggested that molecular testing could lead to a changed therapy recommendation for about one-fifth of patients.

9: TIGIT as a therapeutic target of HPV-positive head and neck squamous cell carcinomas
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Posted 05 Dec 2021

TIGIT as a therapeutic target of HPV-positive head and neck squamous cell carcinomas
132 downloads medRxiv oncology

Xiuning Le, Minghao Dang, Venkatesh L. Hegde, Bo Jiang, Ravaen Slay, Weihong Xiao, Keiko Akagi, Joseph Fresquez, Kathrina L. Marcelo, Qianyun Luo, Pragya Sinha, Ananta V. Yanamandra, Joe Dan Dunn, Diana Bell, Michelle Williams, Edwin Parra, Ryan Goepfert, Stephen H. Lai, Neil Gross, Amit Agrawal, Alexandre Reuben, Jeffrey Myers, Michael A. Curran, K Jagannadha Sastry, Linghua Wang, Maura L Gillison

The tumor immune microenvironment (TIME) of treatment-naive, human papillomavirus-positive head and neck squamous cell carcinoma (HPV-positive HNSCC) was interrogated at single-cell level to identify influential immune checkpoints as therapeutic targets. Single-cell transcriptome profiling revealed enrichment of numerous cell-cell interactions mediated by TIGIT-PVR/NECTIN2 in the TIME of HPV-positive HNSCC versus normal tonsil. TIGIT was the most differentially upregulated immune checkpoint on clonally expanded CD8+ T cells and was abundant on antigen-experienced, tissue-resident memory CD8+ T cell and T-regulatory subsets. TIGIT ligands PVR/NECTIN1/2 were abundant on mature regulatory dendritic cells (DCs), immunosuppressive plasmacytoid DCs, and macrophages. TIGIT and PD-1 co-blockade in the mEER murine model of HPV-positive HNSCC significantly reduced tumor growth, improved survival, restored effector function of HPV16 E7-specific CD8+ T cells, natural killer cells, and DCs, and conferred tumor re-challenge protection. This immunogenetic analysis at single-cell resolution focusing on HPV-positive HNSCC identified TIGIT as a rational therapeutic target.

10: Griffin: Framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA
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Posted 03 Sep 2021

Griffin: Framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA
118 downloads medRxiv oncology

Anna-Lisa Doebley, Minjeong Ko, Hanna Liao, A Eden Cruikshank, Caroline Kikawa, Katheryn Santos, Joseph Hiatt, Robert D Patton, Navonil De Sarkar, Anna C Hoge, Katharine Chen, Zachary T Weber, Mohamed Adil, Jonathan Reichel, Paz Polak, Viktor A Adalsteinsson, Peter S Nelson, Heather A. Parsons, Daniel A Stover, David MacPherson, Gavin Ha

Cell-free DNA (cfDNA) has the potential to inform tumor subtype classification and help guide clinical precision oncology. Here we developed Griffin, a new method for profiling nucleosome protection and accessibility from cfDNA to study the phenotype of tumors using as low as 0.1x coverage whole genome sequencing (WGS) data. Griffin employs a novel GC correction procedure tailored to variable cfDNA fragment sizes, which improves the prediction of chromatin accessibility. Griffin achieved excellent performance for detecting tumor cfDNA in early-stage cancer patients (AUC=0.96). Next, we applied Griffin for the first demonstration of estrogen receptor (ER) subtyping in metastatic breast cancer from cfDNA. We analyzed 254 samples from 139 patients and predicted ER subtype with high performance (AUC=0.89), leading to insights about tumor heterogeneity. In summary, Griffin is a framework for accurate clinical subtyping and can be generalizable to other cancer types for precision oncology applications.

11: Post-Exertional Malaise in People with Chronic Cancer-Related Fatigue
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Posted 15 Dec 2019

Post-Exertional Malaise in People with Chronic Cancer-Related Fatigue
118 downloads medRxiv oncology

Rosemary Twomey, Samuel T. Yeung, James G Wrightson, Guillaume Y Millet, Nicole S. Culos-Reed

ContextCancer-related fatigue (CRF) is a distressing and persistent sense of tiredness or exhaustion that interferes with usual functioning. Chronic CRF continues for months after curative cancer treatment is complete. Post-exertional malaise (PEM) is a worsening of symptoms after physical or mental activity, with limited investigations in people with chronic CRF. ObjectivesThe purpose of this study was to identify and describe self-reported incidences of PEM in people with chronic CRF. MethodsParticipants (n=18) were eligible if they scored [&le;]34 on the Functional Assessment of Chronic Illness Therapy-Fatigue scale and had a cancer-related onset of fatigue. Participants completed a brief questionnaire to assess PEM over a 6-month time-frame (the DePaul Symptom Questionnaire - Post-Exertional Malaise; DSQ-PEM). In addition, a maximal exercise test was used to investigate self-reported symptom exacerbation (via an open-ended questionnaire) after strenuous physical exertion. ResultsOn the DSQ-PEM, three participants met previously defined scoring criteria, which included experiencing moderate to very severe symptoms at least half of the time, worsening of fatigue after minimal effort, plus a recovery duration of >24 h. Content analysis of responses to open-ended questionnaires identified five people who experienced a delayed recovery and symptoms of PEM after maximal exercise. ConclusionA subset of people with chronic CRF (up to 33% in this sample) may experience PEM. Exercise specialists and health care professionals working with people with chronic CRF must be aware that PEM may be an issue. Symptom exacerbation after exercise should be monitored, and exercise should be tailored and adapted to limit the potential for harm. Key messageThis study provides preliminary evidence that a subset of people with chronic cancer-related fatigue experience post-exertional malaise.

12: A deep learning based graph-transformer for whole slide image classification
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Posted 18 Oct 2021

A deep learning based graph-transformer for whole slide image classification
116 downloads medRxiv oncology

Yi Zheng, Rushin Gindra, Margrit Betke, Jennifer Beane, Vijaya B. Kolachalama

Deep learning is a powerful tool for assessing pathology data obtained from digitized biopsy slides. In the context of supervised learning, most methods typically divide a whole slide image (WSI) into patches, aggregate convolutional neural network outcomes on them and estimate overall disease grade. However, patch-based methods introduce label noise in training by assuming that each patch is independent with the same label as the WSI and neglect the important contextual information that is significant in disease grading. Here we present a Graph-Transformer (GT) based framework for processing pathology data, called GTP, that interprets morphological and spatial information at the WSI-level to predict disease grade. To demonstrate the applicability of our approach, we selected 3,024 hematoxylin and eosin WSIs of lung tumors and with normal histology from the Clinical Proteomic Tumor Analysis Consortium, the National Lung Screening Trial, and The Cancer Genome Atlas, and used GTP to distinguish adenocarcinoma (LUAD) and squamous cell carcinoma (LSCC) from those that have normal histology. Our model achieved consistently high performance on binary (tumor versus normal: mean overall accuracy = 0.975+/-0.013) as well as three-label (normal versus LUAD versus LSCC: mean accuracy = 0.932+/-0.019) classification on held-out test data, underscoring the power of GT-based deep learning for WSI-level classification. We also introduced a graph-based saliency mapping technique, called GraphCAM, that captures regional as well as contextual information and allows our model to highlight WSI regions that are highly associated with the class label. Taken together, our findings demonstrate GTP as a novel interpretable and effective deep learning framework for WSI-level classification.

13: mRNA Booster Vaccines Elicit Strong Protection Against SARS-CoV-2 Omicron Variant in Cancer Patients
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Posted 30 Dec 2021

mRNA Booster Vaccines Elicit Strong Protection Against SARS-CoV-2 Omicron Variant in Cancer Patients
109 downloads medRxiv oncology

Cong Zeng, John P. Evans, Karthik Chakravarthy, Panke Qu, Sarah Reisinger, No joon Song, Mark Rubinstein, Peter G. Shields, Zihai Li, Shan-Lu Liu

Following its emergence in late November of 2020, the SARS-CoV-2 Omicron (B.1.1.529) variant has caused major global public health concerns. We recently demonstrated that in healthy adults the Omicron variant exhibits strong resistance to immunity induced by two doses of the mRNA vaccines, but a booster mRNA vaccine dose can provide strong protection against Omicron. However, it is currently unknown how well these mRNA vaccine boosters protect immunocompromised groups, including cancer patients, from the Omicron variant. Here we show that (1) neutralizing antibody (nAb) titers against the Delta and Omicron variants in cancer patients after two-dose mRNA vaccines are 4.2-fold and 21.3-fold lower, respectively, compared to the ancestral D614G, and (2) nAb titers against the Delta and Omicron variants in boosted cancer patients are 3.6-fold and 5.1-fold lower, respectively, compared to D614G. Our findings highlight the effectiveness and need for booster vaccination strategies in immunocompromised groups including cancer patients to protect from the Omicron variant.

14: Comparison of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron Health, SEER, and NPCR
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Posted 18 Mar 2020

Comparison of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron Health, SEER, and NPCR
108 downloads medRxiv oncology

Xinran Ma, Lura Long, Sharon Moon, Blythe J.S. Adamson, Shrujal S. Baxi

Background and ObjectiveThe Surveillance, Epidemiology, and End Results Program (SEER) program and the National Program of Cancer Registries (NPCR), are authoritative sources for population cancer surveillance and research in the US. An increasing number of recent oncology studies are based on the electronic health record (EHR)-derived de-identified databases created and maintained by Flatiron Health. This report describes the differences in the originating sources and data development processes, and compares baseline demographic characteristics in the cancer-specific databases from Flatiron Health, SEER, and NPCR, to facilitate interpretation of research findings based on these sources. MethodsPatients with documented care from January 1, 2011 through May 31, 2019 in a series of EHR-derived Flatiron Health de-identified databases covering multiple tumor types were included. SEER incidence data (obtained from the SEER 18 database) and NPCR incidence data (obtained from the US Cancer Statistics public use database) for malignant cases diagnosed from January 1, 2011 to December 31, 2016 were included. Comparisons of demographic variables were performed across all disease-specific databases, for all patients and for the subset diagnosed with advanced-stage disease. ResultsAs of May 2019, a total of 201,570 patients with 19 different cancer types were included in Flatiron Health datasets. In an overall comparison to national cancer registries, patients in the Flatiron Health databases had similar sex and geographic distributions, but appeared to be diagnosed with later stages of disease and their age distribution differs from the other datasets. For variables such as stage and race, Flatiron Health databases had a greater degree of incompleteness. There are variations in these trends by cancer types. ConclusionsThese three databases present general similarities in demographic and geographic distribution, but there are overarching differences across the populations they cover. Differences in data sourcing (medical oncology EHRs vs cancer registries), and disparities in sampling approaches and rules of data acquisition may explain some of these divergences. Furthermore, unlike the steady information flow entered into registries, the availability of medical oncology EHR-derived information reflects the extent of involvement of medical oncology clinics at different points in the specialty management of individual diseases, resulting in inter-disease variability. These differences should be considered when interpreting study results obtained with these databases.

15: Blood cytokine analysis suggests that SARS-CoV-2 infection results in a sustained tumour promoting environment in cancer patients
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Posted 29 Oct 2021

Blood cytokine analysis suggests that SARS-CoV-2 infection results in a sustained tumour promoting environment in cancer patients
108 downloads medRxiv oncology

Fien HR De Winter, An Hotterbeekx, Manon Huizing, Angelina Konnova, Erik Fransen, Bart 's Jongers, Ravi Kumar Jairam, Vincent Van averbeke, Pieter Moons, Ella Roelant, Debbie Le Blon, Wim Vanden Berghe, Annelies Janssens, Willem Lybaert, Lieselot Croes, Christof Vulsteke, Surbhi Malhotra-Kumar, Herman Goossens, Zwi Berneman, Marc Peeters, Peter van Dam, Samir Kumar-Singh

Cytokines, chemokines and (angiogenic) growth factors (CCGs) have been shown to play an intricate role in the progression of both solid and haematological malignancies. Recent studies have shown that SARS-CoV-2 infection leads to worse outcome in cancer patients, especially in haematological malignancy patients. Here, we investigated how SARS-CoV-2 infection impacts the already altered CCG levels in solid or haematological malignancies, specifically whether there is a protective effect or rather a potentially higher risk for major COVID-19 complications in cancer patients due to elevated CCGs linked to cancer progression. Serially analysing immune responses with 55 CCGs in cancer patients under active treatment with or without SARS-CoV-2 infection, we first showed that cancer patients without SARS-CoV-2 infection (n=54) demonstrate elevated levels of 35 CCGs compared to the non-cancer, non-infected control group of health care workers (n=42). Of the 35 CCGs, 19 were common to both solid and haematological malignancy groups and comprised previously described cytokines such as IL-6, TNF-, IL-1Ra, IL-17A, and VEGF, but also several less well described cytokines/chemokines such as Fractalkine, Tie-2, and T cell chemokine CTACK. Importantly, we show here that 7 CCGs are significantly altered in SARS-CoV-2 exposed cancer patients (n=52). Of these TNF-, IFN-{beta}, TSLP and sVCAM-1, identified to be elevated in haematological cancers, are also known tumour-promoting factors. Longitudinal analysis conducted over 3 months showed persistence of several tumour-promoting CCGs in SARS-CoV-2 exposed cancer patients. These data urge for increased vigilance for haematological malignancy patients as a part of long COVID follow-up.

16: KRAS mutations predict better response to first-line monotherapy with pembrolizumab for patients with PD-L1high metastatic Non-Small Cell Lung Cancer: a retrospective study
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Posted 28 Nov 2021

KRAS mutations predict better response to first-line monotherapy with pembrolizumab for patients with PD-L1high metastatic Non-Small Cell Lung Cancer: a retrospective study
105 downloads medRxiv oncology

Ella A Eklund, Clotilde Wiel, Henrik Fagman, Levent M Akyurek, Sukanya Raghavan, Jan Nyman, Andreas Hallqvist, Volkan I Sayin

Background: Pembrolizumab, a humanized antibody targeting Programmed Cell Death 1 (PD-1), is used as first-line therapy for patients with metastatic Non-Small Cell Lung Cancer (NSCLC) expressing Programmed Death Ligand 1 (PD-L1). However, not all PD-L1 expressing patients respond to pembrolizumab. Thus, there is an urgent need to identify new predictive biomarkers for response to immune checkpoint blockade (ICB) therapy. KRAS mutational status has been suggested to affect treatment outcome, but no clear consensus could be drawn for previous studies. Methods: All consecutive patients diagnosed between 2016-2018 with metastatic NSCLC (stage IV) in the region of West Sweden with molecular characterization available were included in this multi-centers retrospective study. Primary study outcome was overall survival (OS). Baseline patients characteristics, histology type, mutational status, PD-L1 expression and first-line treatment were collected from patient charts and the Swedish Lung Cancer registry. Results: Out of 580 stage IV NSCLC patients, 35.5% harbored a mutation in the KRAS gene (KRASMUT). Compared to KRAS wild-type (KRASWT), KRASMUT was a negative factor for OS (p = 0.014). On multivariate analysis, KRASMUT persisted as a negative factor for OS (HR 1.288, 95% CI 1.091-1.521, p = 0.003). When treated with first-line platinum doublet, KRASMUT (n = 219) is a significant (p = 0.001) negative factor for survival with median OS 9 months vs KRASWT 14 months. Patients on KRAS mutational status and PD-L1 expression levels had a significant better OS in KRASMUT with increased PD-L1 expression (p = 0.036) but not for KRASWT. On first-line ICB, KRASMUT had a significant (p = 0.006) better outcome than KRASWT with a median OS 23 vs 6 months. On multivariable Cox analysis, KRASMUT status and Performance Status (PS) 0-1 were independent prognostic factors for better OS (HR 0.349, 95%CI 0.148-0.822, p = 0.016 and HR 0.398, 95 % CI 0.165-0.963, p =0.041). Conclusions: KRAS mutations combined with PD-L1high is a better predictive marker for response to first-line monotherapy with pembrolizumab than only PD-L1high in patients with metastatic NSCLC.

17: Osteosarcoma: novel prognostic biomarkers using circulating and cell-free tumour DNA
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Posted 14 Dec 2021

Osteosarcoma: novel prognostic biomarkers using circulating and cell-free tumour DNA
95 downloads medRxiv oncology

Iben Lyskjaer, Neesha Kara, Solange De Noon, Christopher Davies, Ana Maia Rocha, Anna-Christina Strobl, Inga Usher, Craig Gerrand, Sandra J Strauss, Daniel Schrimpf, Andreas von Deimling, Stephan Beck, Adrienne M Flanagan

Osteosarcoma (OS) is the most common primary bone tumour in children and adolescents. Despite treatment with curative-intent, many patients die of this disease. Biomarkers for assessment of disease burden and prognoses for osteosarcoma are not available. Circulating-free (cfDNA) and -tumour DNA (ctDNA) are promising biomarkers for disease surveillance in several major cancer types, however only two such studies are reported for OS. In this combined discovery and validation study, we identified four novel methylation-based biomarkers in 171 OS tumours (test set) and comprehensively validated our findings in silico in two independent osteosarcoma sample datasets (n= 162, n=107) and experimentally using digital droplet PCR (ddPCR, n=20 OS tumours). Custom ddPCR assays for these biomarkers were able to detect ctDNA in 40% of pre-operative plasma samples (n=72). ctDNA was detected in 5/17 (29%) post-operative plasma samples from patients who experienced a subsequent relapse post-operatively. Both cfDNA levels and ctDNA detection independently correlated with overall survival, p=0.0015, p=0.0096, respectively. Combining both assays increased the prognostic value of the data. Our findings illustrate the utility of mutation-independent methylation-based markers, broadly applicable ctDNA assays for tumour surveillance and prognostication. This study lays the foundation for multi-institutional collaborative studies to explore the utility of plasma-derived biomarkers for predicting clinical outcome of OS.

18: Proteomics analysis in urinary bladder cancer patients identifies urinary SOD2 as a predictive marker of recurrence
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Posted 14 Dec 2021

Proteomics analysis in urinary bladder cancer patients identifies urinary SOD2 as a predictive marker of recurrence
93 downloads medRxiv oncology

Nitu Kumari, Subasa Chandra Biswal, Shweta Chaudhary, Deepankar Malalkar, Uma S Dubey, Pawan Vasudevae, Anup Kumar, Sunita Saxena, Ranjan Kumar Nanda, Usha Agrawal

Early non-invasive detection of tumor is an urgent clinical need for managing urothelial bladder cancer. Cystoscopy and cytology are the current standards for diagnosis of recurrence, but are limited by low sensitivity. Quantitative proteomics tool was employed to identify important deregulated molecules in bladder cancer tissues and validated using Western blot and immunohistochemistry analysis. A set of 1137 proteins were identified in four paired bladder cancer patients. Among these, 64 proteins were deregulated in all cases among which 9 were commonly up-regulated. The Ingenuity Pathway Analysis (IPA) generated top 11 Networks in which three commonly upregulated (SERPING1, SOD2 and HSPB6) proteins were involved and selected for further validation. Tissue expression of SOD2, SERPING1 and HSPB6 monitored in an independent sample set (n=18) by immuno-histochemical analysis showed similar profile. Western blot analysis of these proteins in urine of bladder cancer (n=26) and healthy subjects (n=10) showed a specificity and sensitivity of >80% for SOD2 and selected for further validation in a separate set (n=150) by ELISA. Significant elevation in urinary SOD2 level was found in urothelial bladder cancer patients compared to healthy controls and in recurrent cases compared to primary (p-value<0.001). Kaplan Meier survival analysis showed urinary SOD2 concentration >2,100 pg/ml was significantly associated with poorer survival and cumulative survival of patient with low SOD2 concentration was 34.4% compared to 18.9% in patient with high SOD2 at 24 months (p=0.025). The study identifies SOD2 as a non-invasive biomarker which may help to extend the period between cystoscopies during follow-up.

19: Collaborative Federated Learning behind Hospitals' Firewalls for Predicting Histological Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer
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Posted 28 Oct 2021

Collaborative Federated Learning behind Hospitals' Firewalls for Predicting Histological Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer
91 downloads medRxiv oncology

Jean Ogier du Terrail, Armand Leopold, Clément Joly, Constance Beguier, Mathieu Andreux, Charles Maussion, Benoit Schmauch, Eric W. Tramel, Etienne Bendjebbar, Mikhail Zaslavskiy, Gilles Wainrib, Maud Milder, Julie Gervasoni, Julien Guerin, Thierry Durand, Alain Livartowski, Kelvin Moutet, Clément Gautier, Inal Djafar, Anne-Laure Moisson, Camille Marini, Mathieu Galtier, Guillaume Bataillon, Pierre-Etienne Heudel

Triple-Negative Breast Cancer (TNBC) is a rare cancer, characterized by high metastatic potential and poor prognosis, and has limited treatment options compared to other breast cancers. The current standard of care in non-metastatic settings is neoadjuvant chemotherapy (NACT), with the goal of breast-conserving surgery and for an in vivo assessment of chemosensitivity. However, the efficacy of this treatment varies significantly across patients, and this histological response heterogeneity is still poorly understood partly due to the paucity of available curated TNBC data. Motivated by this problem, we investigate the use of machine learning (ML) to predict at diagnosis the histological response to NACT for early TNBC patients. To overcome the known biases of related small scale studies while respecting data privacy, we conduct, for the first time, a TNBC study in a multi-centric fashion behind hospitals' firewalls using collaborative Federated Learning (FL). Thereby allowing access to enough TNBC data to sustain a complete response heterogeneity investigation. We show evidence that local ML models relying on Whole-Slide Images (WSIs) at diagnosis are able to predict the histological response to NACT as accurately as current clinical approaches, which rely on time-consuming expert annotations. We demonstrate that collaborative training further improves performance over single-center training outperforming clinical methods. Our ML model is interpretable by design, and we show that it is sensitive to specific histological patterns. While we identify known predictive biomarkers among them, this proof of concept for real-world collaborative FL paves the way for future biomarker discovery using unprecedently large datasets.

20: Multidisciplinary analysis of evolution based Abiraterone treatment for metastatic castrate resistant prostate cancer
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Posted 02 Dec 2021

Multidisciplinary analysis of evolution based Abiraterone treatment for metastatic castrate resistant prostate cancer
87 downloads medRxiv oncology

Jingsong Zhang, Jessica Cunningham, Joel Brown, Robert A Gatenby

Background We present a multidisciplinary approach to clinical trial design and analysis in a pilot study (NCT02415621) in which evolution-based mathematical models guide patient-specific dosing for Abiraterone treatment in men with castrate resistant metastatic prostate cancer. Methods Abiraterone plus prednisone were administered intermittently based on an evolutionary mathematical model. Outcomes are compared to historical controls and a matched contemporaneous cohort who met trial eligibility but received SOC dosing. Longitudinal cohort data allowed modification of pre-trial model parameter estimates. Model simulations of each patient using updated parameters critically evaluated trial design. Results Trial patients, on average, received no abiraterone during 59% of time on treatment. Median Time to Radiographic Progression (TTP) was 30.4 months compared to 14.3 months in the contemporaneous SOC group (p<0.001). All patients in the SOC group have progressed but 4 in the adaptive cohort remain on treatment at >1800 days. Longitudinal trial data found the competition coefficient ratio (RS/SR) of sensitive and resistant populations, a critical factor in intratumoral evolution, was 2 to 3-fold higher than pre-trial estimates. Computer simulations using the corrected parameter unexpectedly demonstrated optimal cycling can reduce the resistant cells. Longitudinal data from 4 trial patients who remain on treatment are consistent with model predictions. Modeling results predict protocol changes that will allow similar outcomes in most patients. Conclusions Administration of abiraterone using evolution-based mathematical models decreased drug dosing and increased radiographic TTP. Integration of mathematical models into trial design identifies novel insights into key treatment parameters and provides optimization strategies for follow-up investigations.

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