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T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates

Cervical cancer is the fourth most common cancer and fourth leading cause of cancer death among women worldwide. In low Human Development Index settings, it ranks second. Screening and surveillance involve the cytology-based Papanicolaou (Pap) test and testing for high-risk human papillomavirus (hrH...

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Autores principales: Christley, Scott, Ostmeyer, Jared, Quirk, Lisa, Zhang, Wei, Sirak, Bradley, Giuliano, Anna R., Zhang, Song, Monson, Nancy, Tiro, Jasmin, Lucas, Elena, Cowell, Lindsay G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050337/
https://www.ncbi.nlm.nih.gov/pubmed/33868241
http://dx.doi.org/10.3389/fimmu.2021.624230
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author Christley, Scott
Ostmeyer, Jared
Quirk, Lisa
Zhang, Wei
Sirak, Bradley
Giuliano, Anna R.
Zhang, Song
Monson, Nancy
Tiro, Jasmin
Lucas, Elena
Cowell, Lindsay G.
author_facet Christley, Scott
Ostmeyer, Jared
Quirk, Lisa
Zhang, Wei
Sirak, Bradley
Giuliano, Anna R.
Zhang, Song
Monson, Nancy
Tiro, Jasmin
Lucas, Elena
Cowell, Lindsay G.
author_sort Christley, Scott
collection PubMed
description Cervical cancer is the fourth most common cancer and fourth leading cause of cancer death among women worldwide. In low Human Development Index settings, it ranks second. Screening and surveillance involve the cytology-based Papanicolaou (Pap) test and testing for high-risk human papillomavirus (hrHPV). The Pap test has low sensitivity to detect precursor lesions, while a single hrHPV test cannot distinguish a persistent infection from one that the immune system will naturally clear. Furthermore, among women who are hrHPV-positive and progress to high-grade cervical lesions, testing cannot identify the ~20% who would progress to cancer if not treated. Thus, reliable detection and treatment of cancers and precancers requires routine screening followed by frequent surveillance among those with past abnormal or positive results. The consequence is overtreatment, with its associated risks and complications, in screened populations and an increased risk of cancer in under-screened populations. Methods to improve cervical cancer risk assessment, particularly assays to predict regression of precursor lesions or clearance of hrHPV infection, would benefit both populations. Here we show that women who have lower risk results on follow-up testing relative to index testing have evidence of enhanced T cell clonal expansion in the index cervical cytology sample compared to women who persist with higher risk results from index to follow-up. We further show that a machine learning classifier based on the index sample T cells predicts this transition to lower risk with 95% accuracy (19/20) by leave-one-out cross-validation. Using T cell receptor deep sequencing and machine learning, we identified a biophysicochemical motif in the complementarity-determining region 3 of T cell receptor β chains whose presence predicts this transition. While these results must still be tested on an independent cohort in a prospective study, they suggest that this approach could improve cervical cancer screening by helping distinguish women likely to spontaneously regress from those at elevated risk of progression to cancer. The advancement of such a strategy could reduce surveillance frequency and overtreatment in screened populations and improve the delivery of screening to under-screened populations.
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spelling pubmed-80503372021-04-17 T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates Christley, Scott Ostmeyer, Jared Quirk, Lisa Zhang, Wei Sirak, Bradley Giuliano, Anna R. Zhang, Song Monson, Nancy Tiro, Jasmin Lucas, Elena Cowell, Lindsay G. Front Immunol Immunology Cervical cancer is the fourth most common cancer and fourth leading cause of cancer death among women worldwide. In low Human Development Index settings, it ranks second. Screening and surveillance involve the cytology-based Papanicolaou (Pap) test and testing for high-risk human papillomavirus (hrHPV). The Pap test has low sensitivity to detect precursor lesions, while a single hrHPV test cannot distinguish a persistent infection from one that the immune system will naturally clear. Furthermore, among women who are hrHPV-positive and progress to high-grade cervical lesions, testing cannot identify the ~20% who would progress to cancer if not treated. Thus, reliable detection and treatment of cancers and precancers requires routine screening followed by frequent surveillance among those with past abnormal or positive results. The consequence is overtreatment, with its associated risks and complications, in screened populations and an increased risk of cancer in under-screened populations. Methods to improve cervical cancer risk assessment, particularly assays to predict regression of precursor lesions or clearance of hrHPV infection, would benefit both populations. Here we show that women who have lower risk results on follow-up testing relative to index testing have evidence of enhanced T cell clonal expansion in the index cervical cytology sample compared to women who persist with higher risk results from index to follow-up. We further show that a machine learning classifier based on the index sample T cells predicts this transition to lower risk with 95% accuracy (19/20) by leave-one-out cross-validation. Using T cell receptor deep sequencing and machine learning, we identified a biophysicochemical motif in the complementarity-determining region 3 of T cell receptor β chains whose presence predicts this transition. While these results must still be tested on an independent cohort in a prospective study, they suggest that this approach could improve cervical cancer screening by helping distinguish women likely to spontaneously regress from those at elevated risk of progression to cancer. The advancement of such a strategy could reduce surveillance frequency and overtreatment in screened populations and improve the delivery of screening to under-screened populations. Frontiers Media S.A. 2021-04-02 /pmc/articles/PMC8050337/ /pubmed/33868241 http://dx.doi.org/10.3389/fimmu.2021.624230 Text en Copyright © 2021 Christley, Ostmeyer, Quirk, Zhang, Sirak, Giuliano, Zhang, Monson, Tiro, Lucas and Cowell https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Christley, Scott
Ostmeyer, Jared
Quirk, Lisa
Zhang, Wei
Sirak, Bradley
Giuliano, Anna R.
Zhang, Song
Monson, Nancy
Tiro, Jasmin
Lucas, Elena
Cowell, Lindsay G.
T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates
title T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates
title_full T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates
title_fullStr T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates
title_full_unstemmed T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates
title_short T Cell Receptor Repertoires Acquired via Routine Pap Testing May Help Refine Cervical Cancer and Precancer Risk Estimates
title_sort t cell receptor repertoires acquired via routine pap testing may help refine cervical cancer and precancer risk estimates
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050337/
https://www.ncbi.nlm.nih.gov/pubmed/33868241
http://dx.doi.org/10.3389/fimmu.2021.624230
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