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Article ; Online: Monolayer culture alters EGFR inhibitor response through abrogation of microRNA-mediated feedback regulation.

Florio, Angela / Johnson, Sarah / Salvatori, Rebecca / Vasmatzis, George

2024 Volume 14, Issue 1, Page(s) 7303

Abstract: Ex vivo drug screening is a potentially powerful tool for the future of cancer care, but the accuracy of results is contingent on the culture model. Both monolayer (2D) and spheroid (3D) culture systems offer advantages, but given the differences in ... ...

Abstract	Ex vivo drug screening is a potentially powerful tool for the future of cancer care, but the accuracy of results is contingent on the culture model. Both monolayer (2D) and spheroid (3D) culture systems offer advantages, but given the differences in mechanical environment, we hypothesized that that the suitability of one system over another would be critical for screening drugs with mechanical targets in mechanical tissues. HCC827 lung adenocarcinoma cells were challenged with EGFR tyrosine kinase inhibitors in monolayer and spheroid culture. RNA sequencing was performed on cells in both conditions to assess culture-induced transcriptional changes that could account for differences in drug response and differences in EGFR expression detected by immunostain. A microRNA microarray was performed to assess culture-induced differences in regulation of microRNA, and the impact of miR-146a-5p on drug response was verified by inhibition. Results were confirmed in human lung adenocarcinoma tissue. HCC827 spheroids were resistant to erlotinib and gefitinib, but significantly more sensitive in 2D culture. RNA-seq and immunostaining show a discrepancy in EGFR transcript and protein expression between the two conditions, which we attribute to miR-146a-5p. This microRNA targets EGFR and is differentially expressed between 2D and 3D culture. Inhibition of miR-146a-5p significantly increased erlotinib cytotoxicity, but validation in patient-derived spheroids suggests that the effect may be mutation-specific. Analysis of RNA-seq data suggests that cells in 2D culture become highly dependent on EGFR signaling to drive proliferation and cell spreading, resulting in a misleading level of sensitivity to EGFR TKIs, while the same cells in spheroid culture retain microRNA-driven EGFR feedback regulation that leaves them less vulnerable to EGFR inhibition. These findings underscore the need for close scrutiny of culture-induced effects on drug target regulation in model design for ex vivo drug screening.
MeSH term(s)	Humans ; MicroRNAs/metabolism ; Carcinoma, Non-Small-Cell Lung/drug therapy ; Carcinoma, Non-Small-Cell Lung/genetics ; Carcinoma, Non-Small-Cell Lung/pathology ; Erlotinib Hydrochloride/pharmacology ; Erlotinib Hydrochloride/therapeutic use ; Lung Neoplasms/drug therapy ; Lung Neoplasms/genetics ; Lung Neoplasms/pathology ; Antineoplastic Agents/pharmacology ; Feedback ; ErbB Receptors/metabolism ; Cell Line, Tumor ; Adenocarcinoma of Lung/drug therapy ; Adenocarcinoma of Lung/genetics ; Protein Kinase Inhibitors/pharmacology ; Protein Kinase Inhibitors/therapeutic use ; Drug Resistance, Neoplasm ; Mutation
Chemical Substances	MicroRNAs ; Erlotinib Hydrochloride (DA87705X9K) ; Antineoplastic Agents ; ErbB Receptors (EC 2.7.10.1) ; Protein Kinase Inhibitors ; EGFR protein, human (EC 2.7.10.1)
Language	English
Publishing date	2024-03-27
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-024-56920-7
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Article ; Online: Evasive Spike Variants Elucidate the Preservation of T Cell Immune Response to the SARS-CoV-2 Omicron Variant.

Solanki, Arnav / Cornette, James / Udell, Julia / Vasmatzis, George / Riedel, Marc

IEEE/ACM transactions on computational biology and bioinformatics

2024 Volume PP

Abstract: The Omicron variants boast the highest infectivity rates among all SARS-CoV-2 variants. Despite their lower disease severity, they can reinfect COVID-19 patients and infect vaccinated individuals as well. The high number of mutations in these variants ... ...

Abstract	The Omicron variants boast the highest infectivity rates among all SARS-CoV-2 variants. Despite their lower disease severity, they can reinfect COVID-19 patients and infect vaccinated individuals as well. The high number of mutations in these variants render them resistant to antibodies that otherwise neutralize the spike protein of the original SARS-CoV-2 spike protein. Recent research has shown that despite its strong immune evasion, Omicron still induces strong T Cell responses similar to the original variant. This work investigates the molecular basis for this observation using the neural network tools NetMHCpan-4.1 and NetMHCiipan-4.0. The antigens presented through the MHC Class I and Class II pathways from all the notable SARS-CoV-2 variants were compared across numerous high frequency HLAs. All variants were observed to have equivalent T cell antigenicity. A novel positive control system was engineered in the form of spike variants that did evade T Cell responses, unlike Omicron. These evasive spike proteins were used to statistically confirm that the Omicron variants did not exhibit lower antigenicity in the MHC pathways. These results suggest that T Cell immunity mounts a strong defense against COVID-19 which is difficult for SARS-CoV-2 to overcome through mere evolution.
Language	English
Publishing date	2024-03-01
Publishing country	United States
Document type	Journal Article
ISSN	1557-9964
ISSN (online)	1557-9964
DOI	10.1109/TCBB.2024.3372100
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Article ; Online: Evaluating NetMHCpan performance on non-European HLA alleles not present in training data.

Atkins, Thomas Karl / Solanki, Arnav / Vasmatzis, George / Cornette, James / Riedel, Marc

Frontiers in immunology

2024 Volume 14, Page(s) 1288105

Abstract: Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare ... ...

Abstract	Bias in neural network model training datasets has been observed to decrease prediction accuracy for groups underrepresented in training data. Thus, investigating the composition of training datasets used in machine learning models with healthcare applications is vital to ensure equity. Two such machine learning models are NetMHCpan-4.1 and NetMHCIIpan-4.0, used to predict antigen binding scores to major histocompatibility complex class I and II molecules, respectively. As antigen presentation is a critical step in mounting the adaptive immune response, previous work has used these or similar predictions models in a broad array of applications, from explaining asymptomatic viral infection to cancer neoantigen prediction. However, these models have also been shown to be biased toward hydrophobic peptides, suggesting the network could also contain other sources of bias. Here, we report the composition of the networks' training datasets are heavily biased toward European Caucasian individuals and against Asian and Pacific Islander individuals. We test the ability of NetMHCpan-4.1 and NetMHCpan-4.0 to distinguish true binders from randomly generated peptides on alleles not included in the training datasets. Unexpectedly, we fail to find evidence that the disparities in training data lead to a meaningful difference in prediction quality for alleles not present in the training data. We attempt to explain this result by mapping the HLA sequence space to determine the sequence diversity of the training dataset. Furthermore, we link the residues which have the greatest impact on NetMHCpan predictions to structural features for three alleles (HLA-A34:01, HLA-C04:03, HLA-DRB1*12:02).
MeSH term(s)	Humans ; Alleles ; Protein Binding ; Histocompatibility Antigens Class I ; Genes, MHC Class I ; Peptides
Chemical Substances	Histocompatibility Antigens Class I ; Peptides
Language	English
Publishing date	2024-01-16
Publishing country	Switzerland
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Comment
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2023.1288105
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Article ; Online: Evaluation of tumor response to immune checkpoint inhibitors by a 3D immunotumoroid model.

Pezeshki, Abdulmohammad / Cheville, John C / Florio, Angela B / Leibovich, Bradley C / Vasmatzis, George

Frontiers in immunology

2024 Volume 15, Page(s) 1356144

Abstract: Background: Only 20 percent of renal and bladder cancer patients will show a significant response to immune checkpoint inhibitor (ICI) therapy, and no test currently available accurately predicts ICI response.: Methods: We developed an " ... ...

Abstract	Background: Only 20 percent of renal and bladder cancer patients will show a significant response to immune checkpoint inhibitor (ICI) therapy, and no test currently available accurately predicts ICI response. Methods: We developed an "immunotumoroid" cell model system that recapitulates the tumor, its microenvironment, and necessary immune system components in patient-derived spheroids to enable ex vivo assessment of tumor response to ICI therapy. Immunotumoroids were developed from surgically resected renal cell carcinomas and bladder carcinomas selected for high tumor-infiltrating lymphocytes (TILs) and survived more than a month without media exchange. Immunohistochemistry was used to detect immune and non-immune cells in cryopreserved source tumors and the resulting immunotumoroids. Immunotumoroid response to ICIs (nivolumab, pembrolizumab, and durvalumab) and chemotherapy (cisplatin, gemcitabine, and paclitaxel) was monitored in real-time with Cytotox Red staining in an Incucyte device, and the immunotumoroid response was compared to retrospective clinical drug responses. Results: Six of the 13 cases tested grew viable immunotumoroid models, with failed cases attributed to extensive tumor tissue necrosis or excess lymphocytes preventing spheroid formation. One successfully cultured case was excluded from the study due to low TIL infiltration (<5%) in the primary tumor sample. The five remaining models contained immune cells (CD4+ and CD8+ T cells, and macrophages), non-immune cells (fibroblasts), and tumor cells. Chemotherapy and ICI drugs were tested in immunotumoroids from 5 cases and compared to clinical outcomes where data was available. Four/five models showed cell killing in response to chemotherapy and two/five showed sensitivity to ICI. In three cases, the immunotumoroid model accurately predicted the patient's clinical response or non-response to ICIs or chemotherapy. Conclusion: Our immunotumoroid model replicated the multicellular nature of the tumor microenvironment sufficiently for preclinical ICI screening. This model could enable valuable insights into the complex interactions between cancer cells, the immune system, and the microenvironment. This is a feasibility study on a small number of cases, and additional studies with larger case numbers are required including correlation with clinical response.
MeSH term(s)	Humans ; Immune Checkpoint Inhibitors/pharmacology ; Immune Checkpoint Inhibitors/therapeutic use ; Retrospective Studies ; Lymphocytes ; Lymphocytes, Tumor-Infiltrating ; Urinary Bladder Neoplasms ; Tumor Microenvironment
Chemical Substances	Immune Checkpoint Inhibitors
Language	English
Publishing date	2024-03-28
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2024.1356144
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Article ; Online: Subtype of SCLC Is an Intrinsic and Persistent Feature Through Systemic Treatment.

Lo, Ying-Chun / Rivera-Concepcion, Joel / Vasmatzis, George / Aubry, Marie-Christine / Leventakos, Konstantinos

JTO clinical and research reports

2023 Volume 4, Issue 9, Page(s) 100561

Abstract: Introduction: SCLC is an aggressive malignancy with poor outcome. Most patients have disease recurrence despite treatments with multiple modalities. Subtyping of SCLC has been proposed recently, and novel agents targeting specific subtypes are actively ... ...

Abstract	Introduction: SCLC is an aggressive malignancy with poor outcome. Most patients have disease recurrence despite treatments with multiple modalities. Subtyping of SCLC has been proposed recently, and novel agents targeting specific subtypes are actively being investigated. In this study, we evaluated the plasticity of subtypes in paired pre- and post-treatment samples. The aim was to understand possible subtype evolution after chemotherapy resistance that could lead to alternate targeted therapy strategies. Methods: A total of 68 samples from 32 patients with sufficient paired specimens were identified from 1998 to 2022. ASCL1, NEUROD1, and POU2F3 immunohistochemistry studies were performed on all cases, and subtyping by predominant expression was determined. Subtype comparison in each patient was performed, and expression analysis was performed on the basis of subtypes. Results: Of 32 cases, 28 (88%) had the same subtype in pre- and first post-treatment specimens. Protein expression level of subtype-specific transcription factor remained stable after chemotherapy. Two of five (40%) NEUROD1-predominant SCLC switched to ASCL1-predominant phenotype after treatment. One case had a pitfall of scoring ASCL1 on specimen with marked crushing artifacts. One case revealed the challenge of proper subtyping for samples with borderline POU2F3 expression. Conclusions: Subtype of SCLC generally remains the same after acquiring chemotherapy resistance. Plasticity was observed with rare cases switching from NEUROD1-predominant to ASC1-predominant SCLC. Resubtyping is unnecessary for the consideration of novel subtype-specific targeted agents, except cases with NEUROD1-predominant subtype.
Language	English
Publishing date	2023-08-16
Publishing country	United States
Document type	Journal Article
ISSN	2666-3643
ISSN (online)	2666-3643
DOI	10.1016/j.jtocrr.2023.100561
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Article: Hydrophobicity identifies false positives and false negatives in peptide-MHC binding.

Solanki, Arnav / Riedel, Marc / Cornette, James / Udell, Julia / Vasmatzis, George

Frontiers in oncology

2022 Volume 12, Page(s) 1034810

Abstract: Major Histocompability Complex (MHC) Class I molecules allow cells to present foreign and endogenous peptides to T-Cells so that cells infected by pathogens can be identified and killed. Neural networks tools such as NetMHC-4.0 and NetMHCpan-4.1 are used ...

Abstract	Major Histocompability Complex (MHC) Class I molecules allow cells to present foreign and endogenous peptides to T-Cells so that cells infected by pathogens can be identified and killed. Neural networks tools such as NetMHC-4.0 and NetMHCpan-4.1 are used to predict whether peptides will bind to variants of MHC molecules. These tools are trained on data gathered from binding affinity and eluted ligand experiments. However, these tools do not track hydrophobicity, a significant biochemical factor relevant to peptide binding, in their predictions. A previous study had concluded that the peptides predicted to bind to HLA-A0201 by NetMHC-4.0 were much more hydrophobic than expected. This paper expands that study by also focusing on HLA-B2705 and HLA-B0801, which prefer binding hydrophilic and balanced peptides respectively. The correlation of hydrophobicity of 9-mer peptides with their predicted binding strengths to these various HLAs was investigated. Two studies were performed, one using the data that the two neural networks were trained on, and the other using a sample of the human proteome. NetMHC-4.0 was found to have a statistically significant bias towards predicting highly hydrophobic peptides as strong binders to HLA-A0201 and HLA-B*2705 in both studies. Machine Learning metrics were used to identify the causes for this bias: hydrophobic false positives and hydrophilic false negatives. These results suggest that the retraining the neural networks with biochemical attributes such as hydrophobicity and better training data could increase the accuracy of their predictions. This would increase their impact in applications such as vaccine design and neoantigen identification.
Language	English
Publishing date	2022-11-07
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2649216-7
ISSN	2234-943X
ISSN	2234-943X
DOI	10.3389/fonc.2022.1034810
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Article: Chromosomal rearrangements and their neoantigenic potential in mesothelioma.

Mansfield, Aaron Scott / Peikert, Tobias / Vasmatzis, George

Translational lung cancer research

2020 Volume 9, Issue Suppl 1, Page(s) S92–S99

Abstract: Chromosomal rearrangements are a defining molecular feature of mesothelioma that are not readily detected by standard DNA sequencing approaches but could be detected by whole genome sequencing methods such as mate-pair sequencing. These chromosomal ... ...

Abstract	Chromosomal rearrangements are a defining molecular feature of mesothelioma that are not readily detected by standard DNA sequencing approaches but could be detected by whole genome sequencing methods such as mate-pair sequencing. These chromosomal rearrangements result in novel, unique gene junctions that can be expressed and potentially result in the presentation of several neoantigens. These predicted neoantigens can be presented by tumors on major histocompatibility complex (MHC) proteins and are correlated with clonal expansion of tumor infiltrating T cells. T cells responsive to these neoantigens have been identified in the circulation of a patient. The predictive values of next generation sequencing-based tumor mutation burden measurements may be significantly enhanced by the addition of techniques such as mate-pair sequencing that can detect chromosomal rearrangements. Furthermore, rearrangement associated neo-antigens may also represent valuable targets for future anti-tumor vaccine strategies. Finally, chromosomal rearrangements are now recognized as a mutation signature in cancer and these events are likely to be important in the oncogenesis and immune recognition of not only in mesothelioma but multiple malignancies including non-small cell lung cancer.
Language	English
Publishing date	2020-02-13
Publishing country	China
Document type	Journal Article ; Review
ZDB-ID	2754335-3
ISSN	2226-4477 ; 2218-6751
ISSN (online)	2226-4477
ISSN	2218-6751
DOI	10.21037/tlcr.2019.11.12
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Article ; Online: Evasive spike variants elucidate the preservation of T cell immune response to the SARS-CoV-2 omicron variant

Solanki, Arnav / Cornette, James / Udell, Julia / Vasmatzis, George / Riedel, Marc

bioRxiv

Abstract	The Omicron variants boast the highest infectivity rates among all SARS-CoV-2 variants. Despite their lower disease severity, they can reinfect COVID-19 patients and infect vaccinated individuals as well. The high number of mutations in these variants render them resistant to antibodies that otherwise neutralize the spike protein of the original SARS-CoV-2 spike protein. Recent research has shown that despite its strong immune evasion, Omicron still induces strong T Cell responses similar to the original variant. This work investigates the molecular basis for this observation using the neural network tools NetMHCpan-4.1 and NetMHCiipan-4.0. The antigens presented through the MHC Class I and Class II pathways from all the notable SARS-CoV-2 variants were compared across numerous high frequency HLAs. All variants were observed to have equivalent T cell antigenicity. A novel positive control system was engineered in the form of spike variants that did evade T Cell responses, unlike Omicron. These evasive spike proteins were used to statistically confirm that the Omicron variants did not exhibit lower antigenicity in the MHC pathways. These results suggest that T Cell immunity mounts a strong defense against COVID-19 which is difficult for SARS-CoV-2 to overcome through mere evolution.
Keywords	covid19
Language	English
Publishing date	2022-11-10
Publisher	Cold Spring Harbor Laboratory
Document type	Article ; Online
DOI	10.1101/2022.11.04.515139
Database	COVID19

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Article ; Online: Complex balanced intrachromosomal rearrangement involving PITX2 identified as a cause of Axenfeld-Rieger Syndrome.

Farris, Joseph / Khanna, Cheryl / Smadbeck, James B / Johnson, Sarah H / Bothun, Erick / Kaplan, Tyler / Hoffman, Francis / Polonis, Katarzyna / Oliver, Gavin / Reis, Linda M / Semina, Elena V / Rust, Laura / Hoppman, Nicole L / Vasmatzis, George / Marcou, Cherisse A / Schimmenti, Lisa A / Klee, Eric W

American journal of medical genetics. Part A

2024 Volume 194, Issue 5, Page(s) e63542

Abstract: Axenfeld-Rieger Syndrome (ARS) type 1 is a rare autosomal dominant condition characterized by anterior chamber anomalies, umbilical defects, dental hypoplasia, and craniofacial anomalies, with Meckel's diverticulum in some individuals. Here, we describe ... ...

Abstract	Axenfeld-Rieger Syndrome (ARS) type 1 is a rare autosomal dominant condition characterized by anterior chamber anomalies, umbilical defects, dental hypoplasia, and craniofacial anomalies, with Meckel's diverticulum in some individuals. Here, we describe a clinically ascertained female of childbearing age with ARS for whom clinical targeted sequencing and deletion/duplication analysis followed by clinical exome and genome sequencing resulted in no pathogenic variants or variants of unknown significance in PITX2 or FOXC1. Advanced bioinformatic analysis of the genome data identified a complex, balanced rearrangement disrupting PITX2. This case is the first reported intrachromosomal rearrangement leading to ARS, illustrating that for patients with compelling clinical phenotypes but negative genomic testing, additional bioinformatic analysis are essential to identify subtle genomic abnormalities in target genes.
MeSH term(s)	Female ; Humans ; Anterior Eye Segment/abnormalities ; Eye Abnormalities/diagnosis ; Eye Abnormalities/genetics ; Eye Abnormalities/pathology ; Eye Diseases, Hereditary/diagnosis ; Eye Diseases, Hereditary/genetics ; Eye Diseases, Hereditary/pathology ; Forkhead Transcription Factors/genetics ; Homeobox Protein PITX2 ; Homeodomain Proteins/genetics
Chemical Substances	Forkhead Transcription Factors ; Homeobox Protein PITX2 (184787-43-7) ; Homeodomain Proteins ; PITX2 protein, human
Language	English
Publishing date	2024-01-17
Publishing country	United States
Document type	Case Reports
ZDB-ID	2108614-X
ISSN	1552-4833 ; 0148-7299 ; 1552-4825
ISSN (online)	1552-4833
ISSN	0148-7299 ; 1552-4825
DOI	10.1002/ajmg.a.63542
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Article ; Online: Unraveling the genomic underpinnings of unbalanced MYC break-apart FISH results using whole genome sequencing analysis.

Gagnon, Marie-France / Penheiter, Alan R / Harris, Faye / Sadeghian, Dorsay / Johnson, Sarah H / Karagouga, Giannoula / McCune, Alexa / Zepeda-Mendoza, Cinthya / Greipp, Patricia T / Xu, Xinjie / Ketterling, Rhett P / McPhail, Ellen D / King, Rebecca L / Peterson, Jess F / Vasmatzis, George / Baughn, Linda B

Blood cancer journal

2023 Volume 13, Issue 1, Page(s) 190

MeSH term(s)	Humans ; Gene Rearrangement ; Genomics/methods ; Whole Genome Sequencing
Language	English
Publishing date	2023-12-19
Publishing country	United States
Document type	Letter ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2600560-8
ISSN	2044-5385 ; 2044-5385
ISSN (online)	2044-5385
ISSN	2044-5385
DOI	10.1038/s41408-023-00967-8
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