Skip to main content
Springer Nature Link
Log in

Finding neoepitopes in mouse models of personalized cancer immunotherapy

  • Review
  • Published:
Save article
View saved research
Frontiers in Biology

Abstract

Background

Cancer immunotherapy uses one’s own immune system to fight cancerous cells. As immune system is hard-wired to distinguish self and non-self, cancer immunotherapy is predicted to target cancerous cells specifically, therefore is less toxic than chemotherapy and radiation therapy, two major treatments for cancer. Cancer immunologists have spent decades to search for the specific targets in cancerous cells.

Methods

Due to the recent advances in high throughput sequencing and bioinformatics, evidence has merged that the neoantigens in cancerous cells are probably the cancer-specific targets that lead to the destruction of cancer.We will review the transplantable murine tumor models for cancer immunotherapy and the bioinformatics tools used to navigate mouse genome to identify tumor-rejecting neoantigens.

Results

Several groups have independently identified point mutations that can be recognized by T cells of host immune system. It is consistent with the note that the formation of peptide-MHC I-TCR complex is critical to activate T cells. Both anchor residue and TCR-facing residue mutations have been reported. While TCR-facing residue mutations may directly activate specific T cells, anchor residue mutations improve the binding of peptides to MHC I molecules, which increases the presentation of peptides and the T cell activation indirectly.

Conclusions

Our work indicates that the affinity of neoepitopes for MHC I is not a predictor for anti-tumor immune responses in mice. Instead differential agretopic index (DAI), the numerical difference of epitope-MHC I affinities between the mutated and un-mutated sequences is a significant predictor. A similar bioinformatics pipeline has been developed to generate personalized vaccines to treat human ovarian cancer in a Phase I clinical trial.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Similar content being viewed by others

Explore related subjects

Discover the latest articles, books and news in related subjects, suggested using machine learning.

References

  • Al Seesi S, Tiagueu Y T, Zelikovsky A, Măndoiu I I (2014). Bootstrapbased differential gene expression analysis for RNA-Seq data with and without replicates. BMC Genomics, 15(8 Suppl 8): S2

    Article  PubMed  PubMed Central  Google Scholar 

  • Basombrio M A (1970). Search for common antigenicities among twenty-five sarcomas induced by methylcholanthrene. Cancer Res, 30(10): 2458–262

    CAS  PubMed  Google Scholar 

  • Bentley D R, Balasubramanian S, Swerdlow H P, Smith G P, Milton J, Brown C G, Hall K P, Evers D J, Barnes C L, Bignell H R, Boutell J M, Bryant J, Carter R J, Keira Cheetham R, Cox A J, Ellis D J, Flatbush MR, Gormley N A, Humphray S J, Irving L J, Karbelashvili M S, Kirk S M, Li H, Liu X, Maisinger K S, Murray L J, Obradovic B, Ost T, Parkinson M L, Pratt M R, Rasolonjatovo I M, Reed M T, Rigatti R, Rodighiero C, Ross M T, Sabot A, Sankar S V, Scally A, Schroth G P, Smith M E, Smith V P, Spiridou A, Torrance P E, Tzonev S S, Vermaas E H, Walter K, Wu X, Zhang L, Alam M D, Anastasi C, Aniebo I C, Bailey D M, Bancarz I R, Banerjee S, Barbour S G, Baybayan PA, Benoit VA, Benson K F, Bevis C, Black P J, Boodhun A, Brennan J S, Bridgham J A, Brown R C, Brown A A, Buermann D H, Bundu A A, Burrows J C, Carter N P, Castillo N, Chiara E, Catenazzi MChang S, Neil Cooley R, Crake N R, Dada O O, Diakoumakos K D, Dominguez-Fernandez B, Earnshaw D J, Egbujor U C, Elmore D W, Etchin S S, Ewan M R, Fedurco M, Fraser L J, Fuentes Fajardo K V, Scott Furey W, George D, Gietzen K J, Goddard C P, Golda G S, Granieri P A, Green D E, Gustafson D L, Hansen N F, Harnish K, Haudenschild C D, Heyer N I, Hims MM, Ho J T, Horgan A M, Hoschler K, Hurwitz S, Ivanov D V, Johnson M Q, James T, Huw Jones T A, Kang G D, Kerelska T H, Kersey A D, Khrebtukova I, Kindwall A P, Kingsbury Z, Kokko-Gonzales P I, Kumar A, Laurent MA, Lawley C T, Lee S E, Lee X, Liao A K, Loch J A, Lok M, Luo S, Mammen R M, Martin J W, McCauley P G, McNitt P, Mehta P, Moon K W, Mullens J W, Newington T, Ning Z, Ling Ng B, Novo S M, O’Neill M J, Osborne M A, Osnowski A, Ostadan O, Paraschos L L, Pickering L, Pike A C, Pike A C, Chris Pinkard D, Pliskin D P, Podhasky J, Quijano V J, Raczy C, Rae V H, Rawlings S R, Chiva Rodriguez A, Roe P M, Rogers J, Rogert Bacigalupo M C, Romanov N, Romieu A, Roth R K, Rourke N J, Ruediger S T, Rusman E, Sanches-Kuiper R M, Schenker M R, Seoane J M, Shaw R J, Shiver M K, Short S W, Sizto N L, Sluis J P, Smith M A, Ernest Sohna Sohna J, Spence E J, Stevens K, Sutton N, Szajkowski L, Tregidgo C L, Turcatti G, Vandevondele S, Verhovsky Y, Virk S M, Wakelin S, Walcott G C, Wang J, Worsley G J, Yan J, Yau L, Zuerlein M, Rogers J, Mullikin J C, Hurles M E, McCooke N J, West J S, Oaks F L, Lundberg P L, Klenerman D, Durbin R, Smith A J (2008). Accurate whole human genome sequencing using reversible terminator chemistry. Nature, 456(7218): 53–59

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Berman J N, Chiu P P L, Dellaire G (2014). Preclinical animal models for cancer genomics. In: Dellair G, Berman J N, Arceci R J, eds. Cancer Genomics: from Bench to Personalized Medicine, Elsevier Inc., 110–126

    Google Scholar 

  • Bielas J H, Loeb K R, Rubin B P, True L D, Loeb L A (2006). From the Cover: Human cancers express a mutator phenotype. Proc Natl Acad Sci USA, 103(48): 18238–18242

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Blanchard T, Srivastava P K, Duan F (2013). Vaccines against advanced melanoma. Clin Dermatol, 31(2): 179–190

    Article  PubMed  Google Scholar 

  • Boland J F, Chung C C, Roberson D, Mitchell J, Zhang X, Im K M, He J, Chanock S J, Yeager M, Dean M (2013). The new sequencer on the block: comparison of Life Technology’s Proton sequencer to an Illumina HiSeq for whole-exome sequencing. Hum Genet, 132(10): 1153–1163

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bolger A M, Lohse M, Usadel B (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics, 30(15): 2114–2120

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Boon T, van der Bruggen P (1996). Human tumor antigens recognized by T lymphocytes. J Exp Med, 183(3): 725–729

    Article  CAS  PubMed  Google Scholar 

  • Castle J C, Kreiter S, Diekmann J, Löwer M, van de Roemer N, de Graaf J, Selmi A, Diken M, Boegel S, Paret C, Koslowski M, Kuhn A N, Britten C M, Huber C, Türeci O, Sahin U (2012). Exploiting the mutanome for tumor vaccination. Cancer Res, 72(5): 1081–1091

    Article  CAS  PubMed  Google Scholar 

  • Cheon D J, Orsulic S (2011). Mouse models of cancer. Annu Rev Pathol, 6(1): 95–119

    Article  CAS  PubMed  Google Scholar 

  • Dranoff G (2012). Experimental mouse tumour models: what can be learnt about human cancer immunology? Nat Rev Immunol, 12(1): 61–66

    CAS  Google Scholar 

  • Duan F, Duitama J, Al Seesi S, Ayres C M, Corcelli S A, Pawashe A P, Blanchard T, McMahon D, Sidney J, Sette A, Baker B M, Mandoiu I I, Srivastava P K (2014). Genomic and bioinformatic profiling of mutational neoepitopes reveals new rules to predict anticancer immunogenicity. J Exp Med, 211(11): 2231–2248

    Article  PubMed  PubMed Central  Google Scholar 

  • Duan F, Lin Y, Liu C, Engelhorn ME, Cohen A D, Curran M, Sakaguchi S, Merghoub T, Terzulli S, Wolchok J D, Houghton A N (2009). Immune rejection of mouse tumors expressing mutated self. Cancer Res, 69(8): 3545–3553

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Duitama J, Srivastava P K, Măndoiu I I (2012). Towards accurate detection and genotyping of expressed variants from whole transcriptome sequencing data. BMC Genomics, 13(2 Suppl 2): S6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Feng J, Meyer C A, Wang Q, Liu J S, Shirley Liu X, Zhang Y (2012). GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. Bioinformatics, 28(21): 2782–2788

    Article  CAS  PubMed  Google Scholar 

  • Foley E J (1953). Antigenic properties of methylcholanthrene-induced tumors in mice of the strain of origin. Cancer Res, 13(12): 835–837

    CAS  PubMed  Google Scholar 

  • Gubin M M, Zhang X, Schuster H, Caron E, Ward J P, Noguchi T, Ivanova Y, Hundal J, Arthur C D, Krebber W J, Mulder G E, Toebes M, Vesely M D, Lam S S, Korman A J, Allison J P, Freeman G J, Sharpe A H, Pearce E L, Schumacher T N, Aebersold R, Rammensee H G, Melief C J, Mardis E R, Gillanders W E, Artyomov M N, Schreiber R D (2014). Checkpoint blockade cancer immunotherapy targets tumour-specific mutant antigens. Nature, 515(7528): 577–581

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kim D, Langmead B, Salzberg S L (2015). HISAT: a fast spliced aligner with low memory requirements. Nat Methods, 12(4): 357–360

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Langmead B, Trapnell C, Pop M, Salzberg S L (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol, 10(3): R25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Larsen M V, Lundegaard C, Lamberth K, Buus S, Lund O, Nielsen M (2007). Large-scale validation of methods for cytotoxic T-lymphocyte epitope prediction. BMC Bioinformatics, 8(1): 424

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li B, Dewey C N (2011). RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics, 12(1): 323

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Liu J, Blake S J, Smyth MJ, Teng MW (2014). Improved mouse models to assess tumour immunity and irAEs after combination cancer immunotherapies. Clin Transl Immunology, 3(8): e22

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lundegaard C, Lund O, Nielsen M (2008). Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers. Bioinformatics, 24(11): 1397–1398

    Article  CAS  PubMed  Google Scholar 

  • Lurquin C, Van Pel A, Mariamé B, De Plaen E, Szikora J P, Janssens C, Reddehase M J, Lejeune J, Boon T (1989). Structure of the gene of tum-transplantation antigen P91A: the mutated exon encodes a peptide recognized with Ld by cytolytic T cells. Cell, 58(2): 293–303

    Article  CAS  PubMed  Google Scholar 

  • Matsushita H, Vesely M D, Koboldt D C, Rickert C G, Uppaluri R, Magrini V J, Arthur C D, White J M, Chen Y S, Shea L K, Hundal J, Wendl M C, Demeter R, Wylie T, Allison J P, Smyth M J, Old L J, Mardis E R, Schreiber R D (2012). Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature, 482(7385): 400–404

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • McGranahan N, Furness A J, Rosenthal R, Ramskov S, Lyngaa R, Saini S K, Jamal-Hanjani M, Wilson G A, Birkbak N J, Hiley C T, Watkins T B, Shafi S, Murugaesu N, Mitter R, Akarca A U, Linares J, Marafioti T, Henry J Y, Van Allen E M, Miao D, Schilling B, Schadendorf D, Garraway L A, Makarov V, Rizvi N A, Snyder A, Hellmann M D, Merghoub T, Wolchok J D, Shukla S A, Wu C J, Peggs K S, Chan T A, Hadrup S R, Quezada S A, Swanton C (2016). Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science, 351(6280): 1463–1469

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo M A (2010). The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res, 20(9): 1297–1303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Monach P A, Meredith S C, Siegel C T, Schreiber H (1995). A unique tumor antigen produced by a single amino acid substitution. Immunity, 2(1): 45–59

    Article  CAS  PubMed  Google Scholar 

  • Nicolae M, Mangul S, Măndoiu I I, Zelikovsky A (2011). Estimation of alternative splicing isoform frequencies from RNA-Seq data. Algorithms Mol Biol, 6(1): 9

    Article  PubMed  PubMed Central  Google Scholar 

  • Noguchi Y, Chen Y T, Old L J (1994). A mouse mutant p53 product recognized by CD4+ and CD8+ T cells. Proc Natl Acad Sci USA, 91(8): 3171–3175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nowell P C (1976). The clonal evolution of tumor cell populations. Science, 194(4260): 23–28

    Article  CAS  PubMed  Google Scholar 

  • Pandey V, Nutter R C, Prediger E (2008). Applied Biosystems SOLiD™ System: Ligation-Based Sequencing. In: Janitz M, ed. Next Generation Genome Sequencing. Wiley-VCH Verlag GmbH & Co. KGaA. p. 29–42

    Chapter  Google Scholar 

  • Prehn R T, Main J M (1957). Immunity to methylcholanthrene-induced sarcomas. J Natl Cancer Inst, 18(6): 769–778

    CAS  PubMed  Google Scholar 

  • Roberts A, Trapnell C, Donaghey J, Rinn J L, Pachter L (2011). Improving RNA-Seq expression estimates by correcting for fragment bias. Genome Biol, 12(3): R22

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Robinson M D, McCarthy D J, Smyth G K (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics, 26(1): 139–140

    Article  CAS  PubMed  Google Scholar 

  • Schmieder R, Edwards R (2011). Quality control and preprocessing of metagenomic datasets. Bioinformatics, 27(6): 863–864

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schuler M M, Nastke M D, Stevanovikć S (2007). SYFPEITHI: database for searching and T-cell epitope prediction. Methods Mol Biol, 409: 75–93

    Article  CAS  PubMed  Google Scholar 

  • Srivastava P K (2015). Neoepitopes of Cancers: Looking Back, Looking Ahead. Cancer Immunol Res, 3(9): 969–977

    Article  CAS  PubMed  Google Scholar 

  • Thomas R K, Nickerson E, Simons J F, Jänne P A, Tengs T, Yuza Y, Garraway L A, LaFramboise T, Lee J C, Shah K, O’Neill K, Sasaki H, Lindeman N, Wong K K, Borras A M, Gutmann E J, Dragnev K H, DeBiasi R, Chen T H, Glatt K A, Greulich H, Desany B, Lubeski C K, Brockman W, Alvarez P, Hutchison S K, Leamon J H, Ronan M T, Turenchalk G S, Egholm M, Sellers WR, Rothberg J M, Meyerson M (2006). Sensitive mutation detection in heterogeneous cancer specimens by massively parallel picoliter reactor sequencing. Nat Med, 12(7): 852–855

    Article  CAS  PubMed  Google Scholar 

  • Tian S, Maile R, Collins E J, Frelinger J A (2007). CD8 + T cell activation is governed by TCR-peptide/MHC affinity, not dissociation rate. J Immunol, 179(5): 2952–2960

    Article  CAS  PubMed  Google Scholar 

  • Trapnell C, Pachter L, Salzberg S L (2009). TopHat: discovering splice junctions with RNA-Seq. Bioinformatics, 25(9): 1105–1111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yadav M, Jhunjhunwala S, Phung Q T, Lupardus P, Tanguay J, Bumbaca S, Franci C, Cheung T K, Fritsche J, Weinschenk T, Modrusan Z, Mellman I, Lill J R, Delamarre L (2014). Predicting immunogenic tumour mutations by combining mass spectrometry and exome sequencing. Nature, 515(7528): 572–576

    Article  CAS  PubMed  Google Scholar 

  • Yates L R, Campbell P J (2012). Evolution of the cancer genome. Nat Rev Genet, 13(11): 795–806

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Immunology and Carole and Ray Neag Comprehensive Cancer Center, University of Connecticut Cancer Center, Farmington, CT, 06030, USA

    Sahar Al Seesi, Alok Das Mohapatra, Arpita Pawashe & Fei Duan

  2. Department of Computer Science & Engineering, University of Connecticut, Storrs, CT, 06269, USA

    Sahar Al Seesi & Ion I. Mandoiu

Authors
  1. Sahar Al Seesi
    View author publications

    Search author on:PubMed Google Scholar

  2. Alok Das Mohapatra
    View author publications

    Search author on:PubMed Google Scholar

  3. Arpita Pawashe
    View author publications

    Search author on:PubMed Google Scholar

  4. Ion I. Mandoiu
    View author publications

    Search author on:PubMed Google Scholar

  5. Fei Duan
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Fei Duan.

Additional information

These authors contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Al Seesi, S., Das Mohapatra, A., Pawashe, A. et al. Finding neoepitopes in mouse models of personalized cancer immunotherapy. Front. Biol. 11, 366–375 (2016). https://doi.org/10.1007/s11515-016-1422-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1007/s11515-016-1422-2

Keywords