Targeting loss of heterozygosity for cancer-specific immunotherapy

Michael S Hwang, Brian J Mog, Jacqueline Douglass, Alexander H Pearlman, Emily Han-Chung Hsiue, Suman Paul, Sarah R DiNapoli, Maximilian F Konig, Drew M Pardoll, Sandra B Gabelli, Chetan Bettegowda, Nickolas Papadopoulos, Bert Vogelstein, Shibin Zhou, Kenneth W Kinzler, Michael S Hwang, Brian J Mog, Jacqueline Douglass, Alexander H Pearlman, Emily Han-Chung Hsiue, Suman Paul, Sarah R DiNapoli, Maximilian F Konig, Drew M Pardoll, Sandra B Gabelli, Chetan Bettegowda, Nickolas Papadopoulos, Bert Vogelstein, Shibin Zhou, Kenneth W Kinzler

Abstract

Developing therapeutic agents with potent antitumor activity that spare normal tissues remains a significant challenge. Clonal loss of heterozygosity (LOH) is a widespread and irreversible genetic alteration that is exquisitely specific to cancer cells. We hypothesized that LOH events can be therapeutically targeted by "inverting" the loss of an allele in cancer cells into an activating signal. Here we describe a proof-of-concept approach utilizing engineered T cells approximating NOT-gate Boolean logic to target counterexpressed antigens resulting from LOH events in cancer. The NOT gate comprises a chimeric antigen receptor (CAR) targeting the allele of human leukocyte antigen (HLA) that is retained in the cancer cells and an inhibitory CAR (iCAR) targeting the HLA allele that is lost in the cancer cells. We demonstrate that engineered T cells incorporating such NOT-gate logic can be activated in a genetically predictable manner in vitro and in mice to kill relevant cancer cells. This therapeutic approach, termed NASCAR (Neoplasm-targeting Allele-Sensing CAR), could, in theory, be extended to LOH of other polymorphic genes that result in altered cell surface antigens in cancers.

Keywords: cancer immunotherapy; cell engineering; chimeric antigen receptor; human leukocyte antigen; loss of heterozygosity.

Conflict of interest statement

Competing interest statement: B.V., K.W.K., and N.P. are founders of Thrive Earlier Detection. K.W.K. and N.P. are consultants to and were on the Board of Directors of Thrive Earlier Detection. B.V., K.W.K., N.P., and S.Z. own equity in Exact Sciences. B.V., K.W.K., N.P., S.Z., and D.M.P. are founders of, hold or may hold equity in, and serve or may serve as consultants to ManaT Bio. B.V., K.W.K., N.P., and S.Z. are founders of, hold equity in, and serve as consultants to Personal Genome Diagnostics. S.Z. has a research agreement with BioMed Valley Discoveries. K.W.K. and B.V. are consultants to Sysmex, Eisai, and CAGE Pharma and hold equity in CAGE Pharma. B.V. is also a consultant to Catalio. K.W.K., B.V., S.Z., and N.P. are consultants to and hold equity in NeoPhore. N.P. is an advisor to and holds equity in CAGE Pharma. C.B. is a consultant to Depuy-Synthes and Bionaut Pharmaceuticals. S.B.G. is a founder and holds equity in AMS. The terms of all these arrangements are being managed by Johns Hopkins University in accordance with its conflict of interest policies. M.F.K. received personal fees from Bristol Myers Squibb and Celltrion. D.M.P. reports grant and patent royalties through institution from Bristol Myers Squibb, a grant from Compugen, stock from Trieza Therapeutics and Dracen Pharmaceuticals, and founder equity from Potenza; being a consultant for Aduro Biotech, Amgen, AstraZeneca (MedImmune/Amplimmune), Bayer, DNAtrix, Dynavax Technologies Corporation, Ervaxx, FLX Bio, Rock Springs Capital, Janssen, Merck, Tizona, and Immunomic Therapeutics; being on the scientific advisory board of Five Prime Therapeutics, Camden Nexus II, and WindMIL; and being on the board of directors for Dracen Pharmaceuticals.

Copyright © 2021 the Author(s). Published by PNAS.

Figures

Fig. 1.
Fig. 1.
An immunotherapeutic approach for targeting LOH. A schema describing the proposed cellular engineering strategy to target LOH events in cancer. Arrows labeled “Allele A” and “Allele B” depict the production of a polymorphic protein as a result of transcription and translation of a polymorphic gene subject to LOH in cancer. The NASCAR platform comprises pairwise CAR and iCAR receptors in T cells. Concurrent engagement of both receptors will result in iCAR-mediated quenching of proximal CAR signaling and divert T cell activation away from normal cells expressing both alleles (Left). However, cancer cells that have undergone LOH will trigger the CAR but not the iCAR, resulting in NASCAR T cell activation (Right).
Fig. 2.
Fig. 2.
Generation of HLA-A allele-targeting scFvs and isogenic cell line models. (A) A2 scFv and (B) A3 scFv binding to various immobilized HLA alleles was assessed by ELISA. Data represent means ± SD of three technical replicates. (C) Flow cytometric evaluation with α-A2 (BB7.2-PE) and α-A3 (GAP.A3-APC) antibodies of HLA KO isogenic cancer cell lines following CRISPR-mediated HLA-A locus disruption.
Fig. 3.
Fig. 3.
Determination of NASCAR specificity in vitro. Three isogenic cancer cell line models of LOH were employed to determine NASCAR specificity. Cancer cells with the indicated HLA-A allele status were coincubated with CAR or NASCAR T cells configured with the indicated allele-targeting CAR and iCAR receptor combinations at an E:T ratio of 2:1. T cell activation was assessed by ELISA for (A) human IFN-γ, hIFN-γ and (B) human IL-2, hIL-2 release. Data represent means ± SD of three technical replicates. (C) Cytotoxicity mediated by CAR or NASCAR T cells was measured by CellTiter-Glo (CFPAC-1, NCI-H441) or Steady-Glo (RPMI-6666). Data represent means ± SD of three technical replicates.
Fig. 4.
Fig. 4.
Evaluation of NASCAR antitumor activity in vivo. (A) A single-flank, subcutaneous (SQ) xenograft model of NSG mice was employed, and CRISPR-engineered A3-CAR T cells or NASCAR T cells targeting A2 loss were introduced via tail vein intravenous (IV) injection 10 d following tumor inoculation. Tumors were measured biweekly for 75 d following tumor inoculation. (B) Tumor growth curves were serially monitored by external caliper measurements. (Insets) Magnified window of the first 45 d of treatment; n = 6 mice per group. Data represent means ± SD; ** and *** denote P ≤ 0.01 and P ≤ 0.001, respectively, as determined by one-way ANOVA with Tukey’s multiple comparison test; ns, not significant.
Fig. 5.
Fig. 5.
Next-generation LOH targeting. (A) NASCAR targeting as applied to genetically unlinked molecules. (B) NASCAR targeting as applied to intracellular polymorphic peptides that are presented on the cell surface in the context of HLA molecules. (C–E) A model of tumor-specific inhibitory markers revealed by LOH that are amenable to NASCAR-based targeting. (F) TAA-specific synNotch receptor-driven conditional expression of a NASCAR expression cassette. TF, transcription factor.

References

    1. Capdeville R., Buchdunger E., Zimmermann J., Matter A., Glivec (STI571, imatinib), a rationally developed, targeted anticancer drug. Nat. Rev. Drug Discov. 1, 493–502 (2002).
    1. Nahta R., Esteva F. J., Trastuzumab: Triumphs and tribulations. Oncogene 26, 3637–3643 (2007).
    1. Weisberg E., Manley P. W., Cowan-Jacob S. W., Hochhaus A., Griffin J. D., Second generation inhibitors of BCR-ABL for the treatment of imatinib-resistant chronic myeloid leukaemia. Nat. Rev. Cancer 7, 345–356 (2007).
    1. Camidge D. R., Pao W., Sequist L. V., Acquired resistance to TKIs in solid tumours: Learning from lung cancer. Nat. Rev. Clin. Oncol. 11, 473–481 (2014).
    1. Oh D.-Y., Bang Y.-J., HER2-targeted therapies—A role beyond breast cancer. Nat. Rev. Clin. Oncol. 17, 33–48 (2020).
    1. Vogelstein B., et al. ., Cancer genome landscapes. Science 339, 1546–1558 (2013).
    1. Cox A. D., Fesik S. W., Kimmelman A. C., Luo J., Der C. J., Drugging the undruggable RAS: Mission possible? Nat. Rev. Drug Discov. 13, 828–851 (2014).
    1. Ostrem J. M. L., Shokat K. M., Direct small-molecule inhibitors of KRAS: From structural insights to mechanism-based design. Nat. Rev. Drug Discov. 15, 771–785 (2016).
    1. Ryan M. B., Corcoran R. B., Therapeutic strategies to target RAS-mutant cancers. Nat. Rev. Clin. Oncol. 15, 709–720 (2018).
    1. Moore A. R., Rosenberg S. C., McCormick F., Malek S., RAS-targeted therapies: Is the undruggable drugged? Nat. Rev. Drug Discov. 19, 533–552 (2020).
    1. Beroukhim R., et al. ., The landscape of somatic copy-number alteration across human cancers. Nature 463, 899–905 (2010).
    1. Garraway L. A., Lander E. S., Lessons from the cancer genome. Cell 153, 17–37 (2013).
    1. Zack T. I., et al. ., Pan-cancer patterns of somatic copy number alteration. Nat. Genet. 45, 1134–1140 (2013).
    1. Knouse K. A., Davoli T., Elledge S. J., Amon A., Aneuploidy in cancer: Seq-ing answers to old questions. Annu. Rev. Cancer Biol. 1, 335–354 (2017).
    1. Nowell P. C., The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).
    1. Mitelman F., Klinger H. P., Catalogue of Chromosome Aberrations in Cancer (Karger Medical and Scientific Publishers, 1983).
    1. Mitelman F., Mertens F., Johansson B., A breakpoint map of recurrent chromosomal rearrangements in human neoplasia. Nat. Genet. 15, 417–474 (1997).
    1. Boveri T., Concerning the origin of malignant tumours by Theodor Boveri. Translated and annotated by Henry Harris. J. Cell Sci. 121, 1–84 (2008).
    1. Vogelstein B., et al. ., Allelotype of colorectal carcinomas. Science 244, 207–211 (1989).
    1. Seymour A. B., et al. ., Allelotype of pancreatic adenocarcinoma. Cancer Res. 54, 2761–2764 (1994).
    1. Radford D. M., et al. ., Allelotyping of ductal carcinoma in situ of the breast: Deletion of loci on 8p, 13q, 16q, 17p and 17q. Cancer Res. 55, 3399–3405 (1995).
    1. Boige V., et al. ., Concerted nonsyntenic allelic losses in hyperploid hepatocellular carcinoma as determined by a high-resolution allelotype. Cancer Res. 57, 1986–1990 (1997).
    1. Lengauer C., Kinzler K. W., Vogelstein B., Genetic instabilities in human cancers. Nature 396, 643–649 (1998).
    1. Haber D. A., et al. ., An internal deletion within an 11p13 zinc finger gene contributes to the development of Wilms’ tumor. Cell 61, 1257–1269 (1990).
    1. Stoler D. L., et al. ., The onset and extent of genomic instability in sporadic colorectal tumor progression. Proc. Natl. Acad. Sci. U.S.A. 96, 15121–15126 (1999).
    1. Shih I.-M., et al. ., Evidence that genetic instability occurs at an early stage of colorectal tumorigenesis. Cancer Res. 61, 818–822 (2001).
    1. Thiagalingam S., et al. ., Mechanisms underlying losses of heterozygosity in human colorectal cancers. Proc. Natl. Acad. Sci. U.S.A. 98, 2698–2702 (2001).
    1. Luo L., Li B., Pretlow T. P., DNA alterations in human aberrant crypt foci and colon cancers by random primed polymerase chain reaction. Cancer Res. 63, 6166–6169 (2003).
    1. Donahue S. L., Lin Q., Cao S., Ruley H. E., Carcinogens induce genome-wide loss of heterozygosity in normal stem cells without persistent chromosomal instability. Proc. Natl. Acad. Sci. U.S.A. 103, 11642–11646 (2006).
    1. Solimini N. L., et al. ., Recurrent hemizygous deletions in cancers may optimize proliferative potential. Science 337, 104–109 (2012).
    1. Xue W., et al. ., A cluster of cooperating tumor-suppressor gene candidates in chromosomal deletions. Proc. Natl. Acad. Sci. U.S.A. 109, 8212–8217 (2012).
    1. Douville C., et al. ., Detection of aneuploidy in patients with cancer through amplification of long interspersed nucleotide elements (LINEs). Proc. Natl. Acad. Sci. U.S.A. 115, 1871–1876 (2018).
    1. Douville C., et al. ., Assessing aneuploidy with repetitive element sequencing. Proc. Natl. Acad. Sci. U.S.A. 117, 4858–4863 (2020).
    1. Basilion J. P., et al. ., Selective killing of cancer cells based on loss of heterozygosity and normal variation in the human genome: A new paradigm for anticancer drug therapy. Mol. Pharmacol. 56, 359–369 (1999).
    1. Fluiter K., et al. ., Tumor genotype-specific growth inhibition in vivo by antisense oligonucleotides against a polymorphic site of the large subunit of human RNA polymerase II. Cancer Res. 62, 2024–2028 (2002).
    1. Fluiter K., et al. ., In vivo tumor growth inhibition and biodistribution studies of locked nucleic acid (LNA) antisense oligonucleotides. Nucleic Acids Res. 31, 953–962 (2003).
    1. Fluiter K., Housman D., Ten Asbroek A. L. M. A., Baas F., Killing cancer by targeting genes that cancer cells have lost: Allele-specific inhibition, a novel approach to the treatment of genetic disorders. Cell. Mol. Life Sci. 60, 834–843 (2003).
    1. Mook O. R. F., Baas F., de Wissel M. B., Fluiter K., Allele-specific cancer cell killing in vitro and in vivo targeting a single-nucleotide polymorphism in POLR2A. Cancer Gene Ther. 16, 532–538 (2009).
    1. Nichols C. A., et al. ., Loss of heterozygosity of essential genes represents a widespread class of potential cancer vulnerabilities. Nat. Commun. 11, 2517 (2020).
    1. Rendo V., et al. ., Exploiting loss of heterozygosity for allele-selective colorectal cancer chemotherapy. Nat. Commun. 11, 1308 (2020).
    1. Mellman I., Coukos G., Dranoff G., Cancer immunotherapy comes of age. Nature 480, 480–489 (2011).
    1. Pardoll D. M., The blockade of immune checkpoints in cancer immunotherapy. Nat. Rev. Cancer 12, 252–264 (2012).
    1. Chen D. S., Mellman I., Oncology meets immunology: The cancer-immunity cycle. Immunity 39, 1–10 (2013).
    1. Schumacher T. N., Schreiber R. D., Neoantigens in cancer immunotherapy. Science 348, 69–74 (2015).
    1. Topalian S. L., Drake C. G., Pardoll D. M., Immune checkpoint blockade: A common denominator approach to cancer therapy. Cancer Cell 27, 450–461 (2015).
    1. Khalil D. N., Smith E. L., Brentjens R. J., Wolchok J. D., The future of cancer treatment: Immunomodulation, CARs and combination immunotherapy. Nat. Rev. Clin. Oncol. 13, 273–290 (2016).
    1. Gotwals P., et al. ., Prospects for combining targeted and conventional cancer therapy with immunotherapy. Nat. Rev. Cancer 17, 286–301 (2017).
    1. Yarchoan M., Johnson B. A. III, Lutz E. R., Laheru D. A., Jaffee E. M., Targeting neoantigens to augment antitumour immunity. Nat. Rev. Cancer 17, 209–222 (2017).
    1. Tran E., Robbins P. F., Rosenberg S. A., ‘Final common pathway’ of human cancer immunotherapy: Targeting random somatic mutations. Nat. Immunol. 18, 255–262 (2017).
    1. Ribas A., Wolchok J. D., Cancer immunotherapy using checkpoint blockade. Science 359, 1350–1355 (2018).
    1. Schumacher T. N., Scheper W., Kvistborg P., Cancer neoantigens. Annu. Rev. Immunol. 37, 173–200 (2019).
    1. Wei S. C., Duffy C. R., Allison J. P., Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discov. 8, 1069–1086 (2018).
    1. Wolchok J., Putting the immunologic brakes on cancer. Cell 175, 1452–1454 (2018).
    1. Zappasodi R., Merghoub T., Wolchok J. D., Emerging concepts for immune checkpoint blockade-based combination therapies. Cancer Cell 33, 581–598 (2018).
    1. Haen S. P., Löffler M. W., Rammensee H.-G., Brossart P., Towards new horizons: Characterization, classification and implications of the tumour antigenic repertoire. Nat. Rev. Clin. Oncol. 17, 595–610 (2020).
    1. Waldman A. D., Fritz J. M., Lenardo M. J., A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nat. Rev. Immunol. 20, 651–668 (2020).
    1. Goebeler M.-E., Bargou R. C., T cell-engaging therapies—BiTEs and beyond. Nat. Rev. Clin. Oncol. 17, 418–434 (2020).
    1. MacKay M., et al. ., The therapeutic landscape for cells engineered with chimeric antigen receptors. Nat. Biotechnol. 38, 233–244 (2020).
    1. Yu J. X., Upadhaya S., Tatake R., Barkalow F., Hubbard-Lucey V. M., Cancer cell therapies: The clinical trial landscape. Nat. Rev. Drug Discov. 19, 583–584 (2020).
    1. Batlevi C. L., Matsuki E., Brentjens R. J., Younes A., Novel immunotherapies in lymphoid malignancies. Nat. Rev. Clin. Oncol. 13, 25–40 (2016).
    1. Neelapu S. S., et al. ., Chimeric antigen receptor T-cell therapy—Assessment and management of toxicities. Nat. Rev. Clin. Oncol. 15, 47–62 (2018).
    1. Teachey D. T., Hunger S. P., Acute lymphoblastic leukaemia in 2017: Immunotherapy for ALL takes the world by storm. Nat. Rev. Clin. Oncol. 15, 69–70 (2018).
    1. Parker K. R., et al. ., Single-cell analyses identify brain mural cells expressing CD19 as potential off-tumor targets for CAR-T immunotherapies. Cell 183, 126–142.e17 (2020).
    1. Neelapu S. S., et al. ., Axicabtagene ciloleucel CAR T-cell therapy in refractory large B-cell lymphoma. N. Engl. J. Med. 377, 2531–2544 (2017).
    1. Sadelain M., Rivière I., Riddell S., Therapeutic T cell engineering. Nature 545, 423–431 (2017).
    1. June C. H., Sadelain M., Chimeric antigen receptor therapy. N. Engl. J. Med. 379, 64–73 (2018).
    1. Maude S. L., et al. ., Tisagenlecleucel in children and young adults with B-cell lymphoblastic leukemia. N. Engl. J. Med. 378, 439–448 (2018).
    1. Schuster S. al. .; JULIET Investigators , Tisagenlecleucel in adult relapsed or refractory diffuse large B-cell lymphoma. N. Engl. J. Med. 380, 45–56 (2019).
    1. Mikkilineni L., Kochenderfer J. N., CAR T cell therapies for patients with multiple myeloma. Nat. Rev. Clin. Oncol., 1–14 (2020).
    1. Wang M., et al. ., KTE-X19 CAR T-cell therapy in relapsed or refractory mantle-cell lymphoma. N. Engl. J. Med. 382, 1331–1342 (2020).
    1. Brown C. E., Mackall C. L., CAR T cell therapy: Inroads to response and resistance. Nat. Rev. Immunol. 19, 73–74 (2019).
    1. Majzner R. G., Mackall C. L., Clinical lessons learned from the first leg of the CAR T cell journey. Nat. Med. 25, 1341–1355 (2019).
    1. Rafiq S., Hackett C. S., Brentjens R. J., Engineering strategies to overcome the current roadblocks in CAR T cell therapy. Nat. Rev. Clin. Oncol. 17, 147–167 (2020).
    1. Watanabe K., Kuramitsu S., Posey A. D. Jr, June C. H., Expanding the therapeutic window for CAR T cell therapy in solid tumors: The knowns and unknowns of CAR T cell biology. Front. Immunol. 9, 2486 (2018).
    1. Lamers C. H. J., et al. ., Treatment of metastatic renal cell carcinoma with autologous T-lymphocytes genetically retargeted against carbonic anhydrase IX: First clinical experience. J. Clin. Oncol. 24, e20–e22 (2006).
    1. Morgan R. A., et al. ., Case report of a serious adverse event following the administration of T cells transduced with a chimeric antigen receptor recognizing ERBB2. Mol. Ther. 18, 843–851 (2010).
    1. Parkhurst M. R., et al. ., T cells targeting carcinoembryonic antigen can mediate regression of metastatic colorectal cancer but induce severe transient colitis. Mol. Ther. 19, 620–626 (2011).
    1. Lamers C. H., et al. ., Treatment of metastatic renal cell carcinoma with CAIX CAR-engineered T cells: Clinical evaluation and management of on-target toxicity. Mol. Ther. 21, 904–912 (2013).
    1. Kloss C. C., Condomines M., Cartellieri M., Bachmann M., Sadelain M., Combinatorial antigen recognition with balanced signaling promotes selective tumor eradication by engineered T cells. Nat. Biotechnol. 31, 71–75 (2013).
    1. Roybal K. T., et al. ., Precision tumor recognition by T cells with combinatorial antigen-sensing circuits. Cell 164, 770–779 (2016).
    1. Lim W. A., June C. H., The principles of engineering immune cells to treat cancer. Cell 168, 724–740 (2017).
    1. Perna F., et al. ., Integrating proteomics and transcriptomics for systematic combinatorial chimeric antigen receptor therapy of AML. Cancer Cell 32, 506–519.e5 (2017).
    1. Cho J. H., Collins J. J., Wong W. W., Universal chimeric antigen receptors for multiplexed and logical control of T cell responses. Cell 173, 1426–1438.e11 (2018).
    1. Fry T. J., et al. ., CD22-targeted CAR T cells induce remission in B-ALL that is naive or resistant to CD19-targeted CAR immunotherapy. Nat. Med. 24, 20–28 (2018).
    1. Srivastava S., et al. ., Logic-gated ROR1 chimeric antigen receptor expression rescues T cell-mediated toxicity to normal tissues and enables selective tumor targeting. Cancer Cell 35, 489–503.e8 (2019).
    1. Fedorov V. D., Themeli M., Sadelain M., PD-1– and CTLA-4–based inhibitory chimeric antigen receptors (iCARs) divert off-target immunotherapy responses. Sci. Trans. Med. 5, 215ra172 (2013).
    1. Snell G. D., Jackson R. B., Histocompatibility genes of the mouse. II. Production and analysis of isogenic resistant lines. J. Natl. Cancer Inst. 21, 843–877 (1958).
    1. Snell G. D., Studies in Histocompatibility. Scand. J. Immunol. 36, 514–525 (1992).
    1. Jiménez P., et al. ., Chromosome loss is the most frequent mechanism contributing to HLA haplotype loss in human tumors. Int. J. Cancer 83, 91–97 (1999).
    1. Little A. M., Parham P., Polymorphism and evolution of HLA class I and II genes and molecules. Rev. Immunogenet. 1, 105–123 (1999).
    1. Mazurenko N. N., et al. ., Genetic alterations at chromosome 6 associated with cervical cancer progression. Mol. Biol. 37, 404–411 (2003).
    1. Robinson J., et al. ., The IPD and IMGT/HLA database: Allele variant databases. Nucleic Acids Res. 43, D423–D431 (2015).
    1. McGranahan al. .; TRACERx Consortium , Allele-specific HLA loss and immune escape in lung cancer evolution. Cell 171, 1259–1271.e11 (2017).
    1. Hahn S. A., Seymour A. B., Allelotype of pancreatic adenocarcinoma using xenograft enrichment. Cancer Res. 55, 4670–4675.
    1. Girard L., Zöchbauer-Müller S., Virmani A. K., Gazdar A. F., Minna J. D., Genome-wide allelotyping of lung cancer identifies new regions of allelic loss, differences between small cell lung cancer and non-small cell lung cancer, and loci clustering. Cancer Res. 60, 4894–4906 (2000).
    1. Maleno I., et al. ., Frequent loss of heterozygosity in the β2-microglobulin region of chromosome 15 in primary human tumors. Immunogenetics 63, 65–71 (2011).
    1. Yeung J. T., et al. ., LOH in the HLA class I region at 6p21 is associated with shorter survival in newly diagnosed adult glioblastoma. Clin. Cancer Res. 19, 1816–1826 (2013).
    1. Garrido M. A., et al. ., HLA class I alterations in breast carcinoma are associated with a high frequency of the loss of heterozygosity at chromosomes 6 and 15. Immunogenetics 70, 647–659 (2018).
    1. Maiers M., Gragert L., Klitz W., High-resolution HLA alleles and haplotypes in the United States population. Hum. Immunol. 68, 779–788 (2007).
    1. Gonzalez-Galarza F. F., et al. ., Allele frequency net database (AFND) 2020 update: Gold-standard data classification, open access genotype data and new query tools. Nucleic Acids Res. 48, D783–D788 (2020).
    1. Parham P., Brodsky F. M., Partial purification and some properties of BB7.2. A cytotoxic monoclonal antibody with specificity for HLA-A2 and a variant of HLA-A28. Hum. Immunol. 3, 277–299 (1981).
    1. Berger A. E., Davis J. E., Cresswell P., Monoclonal antibody to HLA-A3. Hybridoma 1, 87–90 (1982).
    1. Miller M. S., et al. ., An engineered antibody fragment targeting mutant β-catenin via major histocompatibility complex I neoantigen presentation. J. Biol. Chem. 294, 19322–19334 (2019).
    1. Eyquem J., et al. ., Targeting a CAR to the TRAC locus with CRISPR/Cas9 enhances tumour rejection. Nature 543, 113–117 (2017).
    1. Liu Z., et al. ., Systematic comparison of 2A peptides for cloning multi-genes in a polycistronic vector. Sci. Rep. 7, 2193 (2017).
    1. Skora A. D., et al. ., Generation of MANAbodies specific to HLA-restricted epitopes encoded by somatically mutated genes. Proc. Natl. Acad. Sci. U.S.A. 112, 9967–9972 (2015).
    1. Tran E., et al. ., Immunogenicity of somatic mutations in human gastrointestinal cancers. Science 350, 1387–1390 (2015).
    1. Leko V., Rosenberg S. A., Identifying and targeting human tumor antigens for T cell-based immunotherapy of solid tumors. Cancer Cell 38, 454–472 (2020).
    1. Wu D., Gallagher D. T., Gowthaman R., Pierce B. G., Mariuzza R. A., Structural basis for oligoclonal T cell recognition of a shared p53 cancer neoantigen. Nat. Commun. 11, 2908 (2020).
    1. Fountain J. W., et al. ., Homozygous deletions within human chromosome band 9p2l in melanoma. Med. Sci. 89, 10557–10561.
    1. Narimatsu H., et al. ., Lewis and secretor gene dosages affect CA19-9 and DU-PAN-2 serum levels in normal individuals and colorectal cancer patients. Cancer Res. 58, 512–518 (1998).
    1. Yan H., Yuan W., Velculescu V. E., Vogelstein B., Kinzler K. W., Allelic variation in human gene expression. Science 297, 1143 (2002).
    1. Sade-Feldman M., et al. ., Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat. Commun. 8, 1136 (2017).
    1. Orlando E. J., et al. ., Genetic mechanisms of target antigen loss in CAR19 therapy of acute lymphoblastic leukemia. Nat. Med. 24, 1504–1506 (2018).
    1. Tran E., et al. ., T-cell transfer therapy targeting mutant KRAS in cancer. N. Engl. J. Med. 375, 2255–2262 (2016).
    1. Chowell D., et al. ., Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 359, 582–587 (2018).
    1. Montes P., et al. ., Genomic loss of HLA alleles may affect the clinical outcome in low-risk myelodysplastic syndrome patients. Oncotarget 9, 36929–36944 (2018).
    1. Chen H., et al. ., Genomic and immune profiling of pre-invasive lung adenocarcinoma. Nat. Commun. 10, 5472 (2019).
    1. Lo W., et al. ., Immunologic recognition of a shared p53 mutated neoantigen in a patient with metastatic colorectal cancer. Cancer Immunol. Res. 7, 534–543 (2019).
    1. Tamaki K., et al. ., Somatic mutations and loss of heterozygosity of HLA genes are frequently occurred and tightly associated with poor prognosis in adult T cell leukemia-lymphoma. Blood 134, 2785 (2019).
    1. Shim J. H., et al. ., HLA-corrected tumor mutation burden and homologous recombination deficiency for the prediction of response to PD-(L)1 blockade in advanced non-small-cell lung cancer patients. Ann. Oncol. 31, 902–911 (2020).
    1. Hamburger A. E., et al. ., Engineered T cells directed at tumors with defined allelic loss. Mol. Immunol. 128, 298–310 (2020).
    1. Martayan A., et al. ., Class I HLA folding and antigen presentation in β 2-microglobulin-defective Daudi cells. J. Immunol. 182, 3609–3617 (2009).
    1. Haidaris C. G., et al. ., Recombinant human antibody single chain variable fragments reactive with Candida albicans surface antigens. J. Immunol. Methods 257, 185–202 (2001).
    1. Nguyen D. N., et al. ., Polymer-stabilized Cas9 nanoparticles and modified repair templates increase genome editing efficiency. Nat. Biotechnol. 38, 44–49 (2020).

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe