Novel antibody cocktail therapy targeting extracellular tumor-specific mutations to treat triple-negative breast cancer

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Pero, Girja S. Shukla, Yujing Sun, Ramiro Barrantes-Reynolds, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6073571/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Treatment options for triple-negative breast cancer (TNBC) remain limited, and the highly heterogeneous nature of these tumors often contributes to therapeutic resistance. While we have previously demonstrated that preparing a cocktail of antibodies targeting multiple distinct mutated cell surface proteins (MSPs) harboring neoepitopes unique to a given tumor can effectively disrupt tumor growth in mice, the feasibility of this approach in treating TNBC has yet to be tested. Methods We used the murine EMT6 cell line to model TNBC, comparing the EMT6 cell genome to that of parental BALB/c mice to guide the production of polyclonal antibodies (pAbs) targeting 12 different EMT6-specific MSPs. Antibody binding to purified peptides, EMT6 cells, and healthy tissues was assessed through immunofluorescence staining. EMT6 tumor-bearing mice were established and treated with a pAb cocktail in combination with anti-PD-1, and tumor growth and survival were monitored. A bioinformatics-based survey of genomic data from TNBC patients in The Cancer Genome Atlas (TCGA) database was conducted to assess MSP prevalence. Results Of the 12 pAb preparations, 9 successfully bound to EMT6 cell surfaces in a cumulative manner without detectable non-tumor binding. When we administered a cocktail of these 9 MSP-targeting pAbs to EMT6 tumor-bearing mice, delayed tumor growth and improved survival were observed. Analyses of the TCGA cohort of TNBC patients revealed that the tumors of a larger proportion of these patients harbored > 10 MSPs as compared to individuals with other forms of breast cancer (69% vs. 42%), making them particularly good candidates for MSP-specific antibody cocktail treatment. Conclusions Together, these results highlight the promise of using antibodies directed against MSPs expressed by TNBC tumor cells to kill tumor cells in vivo , providing a unique approach to individualized cancer patient care with the potential to achieve superior patient outcomes through the elimination of heterogeneous tumor cell populations. Triple-negative breast cancer mutated cell surface protein-targeting antibodies somatic missense mutation antibody-dependent cellular cytotoxicity tumor growth inhibition Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 BACKGROUND Tumor growth entails the acquisition of additional mutations and the consequent emergence of increasingly heterogeneous cell populations ( 1 , 2 ). Even when available treatments achieve a clinical complete response, the expansion of small populations of treatment-resistant tumor cells often leads to recurrence and drug resistance following successful treatment ( 3 – 5 ), which is a persistent challenge to effective breast cancer management ( 6 ). While recent combination regimens have conferred survival advantages to subsets of breast cancer patients with recurrent disease ( 7 – 9 ), they have not fully resolved the underlying challenge of drug resistance. This is a particularly pressing clinical challenge for patients with triple-negative breast cancer (TNBC) for whom fewer treatment options are available. In the neoadjuvant setting, patients with TNBC exhibit a higher rate of complete response with the addition of checkpoint inhibitors, but incomplete tumor eradication remains a problem ( 10 ). Targeted immune therapies, including monoclonal antibodies, vaccines, and T-cell therapies, must therefore be capable of overcoming tumor heterogeneity to contribute to better patient outcomes. We have focused on addressing the challenge of intratumoral heterogeneity by leveraging the firmly established ability of immune effector cells to clear antibody-opsonized target cells ( 11 , 12 ). TNBC patients lack any universal surface markers that can be safely and effectively targeted with therapeutic antibodies in a manner akin to the trastuzumab-based treatment of HER2 + breast cancer ( 13 ). However, TNBC is characterized by a higher mutational burden than other forms of breast cancer ( 14 ), with elevated rates of random genomic mutation contributing to the generation of immunologically novel protein epitopes (here referred to as neoepitopes) expressed in tumors but not normal tissues. These neoepitopes are ideal targets for a range of therapeutic interventions, including tumor vaccines, adoptive T cell therapy, and antibody-based treatment ( 15 ), as they are tumor cell-specific. We refer to the cell surface proteins harboring these neoepitopes as m utated cell s urface p roteins (MSPs). As opposed to “driver” mutations, these MSPs are generated in a largely random manner, they are almost all patient-specific, with overlap among patients being largely attributable to chance. Effective antibody-based neoepitope targeting therefore relies on the production of these antibodies for each patient individually. While this personalized approach may once have been considered infeasible, the COVID-19 pandemic accelerated the development of methods suitable for more rapidly producing therapeutic antibodies ( 16 ). We have leveraged and further optimized these techniques to establish a pipeline for the rapid identification of suitable tumor-specific MSP targets and the small-batch production of custom cocktails of antibodies targeting multiple MSPs for individual patients ( 17 ). This approach takes advantage of the heterogeneity inherent within tumors by directing immune cells to clear tumor cells bearing myriad distinct surface neoepitopes. We have been able to successfully prolong the survival of tumor-bearing mice by administering tumor-specific cocktails of MSP-targeting antibodies, without any adverse normal tissue pathology ( 18 ). However, the feasibility of using this individualized approach to treat TNBC has not been assessed to date. Given the lack of consistent target availability among TNBC patients and high rates of tumor recurrence attributable to the heterogeneity of tumor cell subpopulations, in this study we sought to exploit the neoepitope space conferred by such heterogeneity to investigate the feasibility of treating TNBC using MSP-targeting antibodies using the EMT6 TNBC mouse model. We also surveyed sequencing data from breast cancer patients to highlight the potential amenability of human TNBC to this MSP-targeting antibody treatment strategy, underscoring its promise as a novel individualized approach with the potential to prolong survival and quality of life for patients who currently lack reliable therapeutic options. METHODS Cells and Reagents EMT6/P cells (Sigma-Aldrich) were cultured according to the manufacturer’s instructions in EMEM containing 10% fetal bovine serum (FBS; Sigma), 2 mM glutamine, 1% non-essential amino acids (Sigma), and penicillin/streptomycin (Sigma). Goat serum was obtained from Jackson Immunoresearch. Antibodies used for this study included anti-mouse PD-1 (CD279; clone RMP1-14; Bio X cell), rabbit IgG, goat anti-rabbit IgG (H + L) cross-adsorbed secondary antibody Alexa Fluor® 568 conjugate (Invitrogen), and anti-Rabbit IgG Fc Monoclonal Secondary Antibody HRP conjugate (GenScript). Other reagents included paraformaldehyde (16% solution, EM Science, USA), DAPI (Invitrogen), fluorescent mounting medium (DAKO), Casein-TBS blocker (Pierce), soluble 3,3',5,5'-Tetramethylbenzidine (TMB; EMD Millipore), low-IgG FBS (Gibco). All other chemicals were of the highest quality grade and obtained from commercial sources. Missense Mutation Localization Whole exome sequencing and variant data for the EMT6/P cell line were received from Charles River Laboratories. The human patient somatic mutation information and variant calls were obtained from the open access collection of The Cancer Genome Atlas Project (TCGA; https://www.cancer.gov/tcga ) with available matching tumor and normal blood data. To identify the subcellular localization of each missense mutation, the UniProtID mapping service was used ( 19 , 20 ). First, the correct UniProtID for each gene was identified to ensure the correct isoform was considered. Entries with no UniProtID were eliminated as data on subcellular localization could not be obtained. For each UniProtID, annotated subcellular location information was obtained from Uniprot using the uniprotR package ( https://cran.r-project.org/web/packages/UniprotR/citation.html ). Given the variant position in the gene, the exact subcellular location of the variant was identified, including whether the variant was in the extracellular domain or located on a secreted protein. Programming was performed using the R programming language ( 21 ) and reports were generated using RStudio ( 22 ). Missense mutation-related information was extracted from the TCGA database, including Estrogen Receptor (ER)/Progesterone Receptor (PR) / human epidermal growth factor receptor 2 (HER2) status, HUGO gene symbol, position in the chromosome, and precise variant information. Our patient dataset included 100 TNBC patients (ER − /PR − /HER2 − ) and 83 other breast cancer patients, providing a broad spectrum of genetic information for analysis. The number of MSP neoepitopes for each patient was calculated by adding together the following: ( 1 ) the number of mutations identified in protein extracellular domains, ( 2 ) the number of mutations identified within secreted proteins, and ( 3 ) 50% of the mutations located in cell surface-associated proteins for which an exact location was not defined. Cell surface-associated proteins were defined as those proteins associated with terms in the UniProt database including apical cell membrane, cell membrane, multi- and single-pass membrane protein, and peripheral membrane proteins. The 50% hit rate for membrane proteins without a defined extracellular domain was determined based on the percent favorable (extracellular domain or secreted) mutations on defined extracellular proteins. Peptide Synthesis Peptides (11–14 amino acids) including target mutated residues and adjacent amino acids that were predicted to be immunogenic in rabbits were designed by GenScript (Table 1 ). Peptides were synthesized to have an N- or C-terminal cysteine for conjugation to keyhole limpet hemocyanin (KLH). Before conjugation, each peptide was purified using high-performance liquid chromatography at > 95% purity, and mass spectrometry was performed to confirm sequence identity. Unconjugated peptides were used for ELISA analysis. KLH-conjugated peptides were used for rabbit immunization for antibody production. Antibody Production and Characterization Purified antibody production and ELISA-based characterization were performed using methods previously reported ( 17 ). Immunization of 2 rabbits per peptide using the polyexpress protocol by Genscript. Antibodies were purified by affinity purification with the peptide immunogen. Final antibodies were dissolved in PBS with no additives. For ELISAs, the rabbit pAbs capable of binding to mutated peptide-coated wells (4 µg/ml) were detected using HRP-conjugated anti-rabbit IgG Fc (Genscript) and soluble TMB, measuring absorbance at 650 nm (A 650 ). Antibody-Dependent Cellular Cytotoxicity (ADCC) Assay EMT6/P cells (20,000 cells/well) were seeded in a U-bottom 96-well plate (Falcon) in media containing low-IgG FBS. Peripheral blood mononuclear cells (PBMCs) were isolated from freshly collected healthy human donor blood (UVM IRB approved protocol #0000317) using Accuspin tubes with Histopaque-1077 (Sigma), according to the manufacturer’s instructions. PBMCs (effector cells) were resuspended in serum-free CTL-Test medium (Cellular Technology Limited) with freshly added L-glutamine (2 mM, Gibco). PBMCs were added to target cells at varying ratios. Each well was treated with the 9 pAb-cocktail (1 µg total, mixing antibodies in equal amounts), control rabbit polyclonal IgG (1 µg), or no antibody, in triplicate. The cells were placed at 37°C in a 5% CO 2 humidified incubator for 21 h. ADCC was assessed using the LDH-Glo Cytotoxicity Assay Kit (Promega) according to the manufacturer’s instructions. Plates were analyzed using a microplate luminometer (Turner Biosystems). EMT6/P control wells were treated with 2 µL of 10% Triton X‐100 for 30 min to lyse the cells as the maximum release control wells. Percent cytotoxicity was calculated as follows: [(Experimental – Effector Spontaneous – Target Spontaneous)/(Target Maximum – Target Spontaneous)] × 100. Animal Care Animal procedures used in this study were approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Vermont (Protocol # 18 − 002). The syngeneic EMT6 tumor model used for this study was derived from the propagation of hyperplastic alveolar nodules transplanted in BALB/c mice ( 23 ). This tumor epithelial cell line shows characteristics of triple-negative breast tumors. Female BALB/c (6–7 weeks old) were obtained from the Jackson Laboratory (Bar Harbor, ME, USA). Mice were kept in an animal facility with standard ventilation and lighting (12-hour light/dark cycles), and free access to food pellets and water. Mice were allowed to acclimate for one week, after which they were numbered, and their right flank was shaved for tumor implantation. Animal Treatments An initial experiment was performed to determine the optimal number of EMT6/P tumor cells inoculation for producing a tumor with a ~ 2000 mm 3 volume in 15–20 days. EMT6/P cells were grown in standard culture medium until ~ 70% confluent, at which time they were harvested, washed with PBS, and suspended in PBS at the desired concentration. We subcutaneously injected 3 groups (n = 5) of BALB/c mice with 0.5 x 10 6 , 1 x 10 6 , or 1.5 x 10 6 EMT6/P breast tumor cells suspended in 0.1 mL of PBS. In the subsequent experiment, the effect of treatment with a cocktail of rabbit pAbs directed against mutated peptides on EMT6/P tumor growth and murine survival was assessed. In total, 24 BALB/c mice were subcutaneously implanted with 1 x 10 6 tumor cells in the shaved right flank. These tumor-implanted mice were then randomized into four groups (n = 6/group) and treated as follows: Group 1. No treatment Group 2. PD1i only: Mice were each intraperitoneally injected with 0.2 mg of rat anti-mouse PD-1 (CD279; clone RMP1-14) at 3, 5, 7, 9, and 11 days post-implantation (DPI). Group 3. Rabbit polyclonal IgG + PD1i: Mice were each subcutaneously injected with 0.2 mg at the tumor base of normal rabbit IgG at 3, 4, 5, 6, and 7 DPI, and were intraperitoneally injected with 0.2 mg of rat anti-mouse PD-1 (CD279; clone RMP1-14) at 3, 5, 7, 9, and 11 DPI. Group 4. pAb Cocktail + PD1i: Mice were each subcutaneously injected at the tumor base with 0.2 mg of a cocktail of 9 pAb directed against mutated peptides at 3, 4, 5, 6, and 7 DPI, and were intraperitoneally injected with 0.2 mg of rat anti-mouse PD-1 (CD279; clone RMP1-14) at 3, 5, 7, 9, and 11 DPI. Tumor Growth and Animal Survival Electronic calipers were used to track tumor growth daily beginning at 7 DPI, and the tumor volume was calculated as follows: V = (W 2 × L)/2, where V, W, and L respectively denote the tumor volume, width, and length. Survival time was recorded based on animal death or humane endpoints (tumor volume ≥ 2000 mm 3 , or symptoms of physical distress such as dehydration, difficulty walking, cachexia, or other symptoms) per an established IACUC protocol. The body weights of tumor-bearing mice were measured twice weekly to track their overall health. Immunofluorescence Microscopy EMT6/P tumors were harvested from BALB/c mice, while normal tissues (lung, liver, brain, heart, kidney, and spleen) were harvested from untreated BALB/c mice. Harvested tissues were snap-frozen, stored at -80°C, and sectioned (5 µm) on glass slides for staining. Cell and tissue staining were performed as reported previously ( 17 ). Alexa Fluor 568 goat-anti-rabbit IgG (H + L) (Invitrogen) was used to detect targeted rabbit antibody binding. Statistical Analyses Tumor growth was compared among animals in different treatment groups with two-way ANOVA and Tukey's multiple comparison test. Kaplan-Meier plots and log-rank (Mantel-Cox) tests were used to compare survival differences among groups. The 95% confidence intervals (CIs) for median survival and corresponding hazard ratios were estimated. GraphPad Prism (San Diego, CA, USA) was used for data analysis and figure preparation. Further details regarding experimental tests and replicates are described in figure legends. RESULTS EMT6 tumor cells express surface neoepitopes suitable for antibody-based targeting To assess the preclinical feasibility of using a cocktail of oligoclonal MSP-targeting antibodies to treat TNBC in vivo , we selected the murine EMT6 cell line as it is a syngeneic immunocompetent model that has been extensively used in previous TNBC studies ( 23 , 24 ). When we conducted a mutational analysis of EMT6 cells, we identified 1,252 total somatic missense mutations, of which 104 were located within regions encoding the extracellular domains (ECDs) of membrane proteins. These 104 mutations were present across 92 genes harboring a single mutation, as well as 6 genes harboring two mutations each ( Folh1, Grid2, Grik1, Lepr, Ptprb , and Sort1 ) in EMT6 cells. The identified mutations included known cancer driver mutations in 5 ECD targets and 1 secreted protein. We generated pAbs targeting 12 different MSPs in EMT6 cells using a mutated peptide vaccination approach based on these identified somatic missense mutations. Following vaccination with peptides containing the appropriate amino acid substitution corresponding to each mutation, antibodies directed against each MSP neoepitope were affinity-enriched from the serum of vaccinated rabbits. We successfully prepared high-titer antibodies specific for all 12 targets with ≥ 95% purity and strong binding affinity for their cognate antigens (Table 1 , Fig. 1 ). When tested for binding to the surface of EMT6 cells, 9 of the 12 pAbs exhibited positive binding (Fig. 2 a). Strikingly, when these antibodies were combined, a progressive increase in fluorescent signal was observed on the surface of EMT6 cells as the number of pAbs targeting different MSPs increased (Fig. 2 b). In contrast, even at the highest concentration tested, the polyclonal IgG from control rabbits failed to yield a significant immunofluorescent signal compared to the pAbs. Table 1 Characteristics of prepared pAbs targeting 12 EMT6 tumor-associated MSPs No. Protein Name_Mutation site Mutated Peptide Vaccine Purity Titer EC50 (M) 1 Dcbld2_N416K YHKDVRN K FLPC 98% > 1:512000 6.18E-11 2 Folh1_S550T WKTNKVS T YPLC 99% > 1:512000 2.76E-11 3 Mfsd14b_N320T CKLMRSLG T KNT 96% 1:512000 3.62E-11 4 Mep1b_F242L VIGQRMD L SDYDC 98% > 1:512000 2.57E-11 5 Grik1_T548P CLYRKPNG P NPG 96% 1:512000 1.07E-10 6 Dscam_S212R CGETRQSN R ARL 98% > 1:512000 3.68E-11 7 Pcdha7_A381G VFDRDSG G NGQC 95% > 1:512000 5.84E-11 8 Cdh20_A534P CYSL P PEAANNP 95% > 1:512000 4.01E-11 9 Sort1_R434W QGG W WEHLRKPENC 99% 1:512000 1.71E-10 10 Tarm1_E77D NSVKPYNLT D ETAC 98% > 1:512000 1.23E-11 11 Mmp14_P316S PKNPAYG S NIC 98% > 1:512000 2.24E-11 12 Il1rl2_P62A YKT A SKSPVSNC 96% > 1:512000 1.59E-11 NOTE: Mutated amino acids are highlighted in boldface text. MSP-targeting antibody cocktail treatment kills target tumor cells and prolongs survival To evaluate the specificity of a cocktail prepared from these 9 pAbs, they were next used for the immunofluorescent staining of EMT6 tumors or healthy major organs from BALB/c mice. While the 9-pAb cocktail exhibited strong binding to EMT6 tumors, no binding above background levels was noted for healthy lungs, brain, heart, liver, spleen, or kidneys (Fig. 3 ), confirming the tumor-specific binding of these MSP-targeting antibodies. To examine the ability of this 9-pAb cocktail to mediate target tumor cell killing, an antibody-dependent cellular cytotoxicity (ADCC) assay was performed in which EMT6 cells were co-cultured with healthy donor peripheral blood mononuclear cells (PBMCs) at a range of PBMC: target cell ratios (100:1, 50:1, 25:1) in the presence of 9-pAb cocktail or control polyclonal IgG. Cytotoxicity was then analyzed after 21 h using a lactate dehydrogenase (LDH) release assay, revealing that the 9-pAb cocktail was able to induce high levels of EMT6 cell death, including > 80% death at a 100:1 PBMC: target cell ratio (Fig. 4 ). Given its preferential tumor-specific binding and ability to readily facilitate ADCC-dependent EMT6 tumor cell killing, we tested the ability of the 9-pAb cocktail to prevent EMT6 tumor growth in vivo . To that end, BALB/c mice were subcutaneously implanted in the right flank with 1x10 6 EMT6 cells. Beginning 3 days post-implantation, mice were subcutaneously injected with the 9-pAb cocktail or control polyclonal IgG (0.2 mg/day) at the tumor base daily for 5 days. In addition, 0.2 mg of rat anti-mouse PD-1 was intraperitoneally injected into these mice on days 3, 5, 7, 9, and 11 after tumor implantation (Fig. 5 a). In this experiment, combined 9-pAb cocktail and anti-PD-1 treatment was associated with significantly reduced tumor growth and significantly prolonged murine survival (Fig. 5 b, c and Tables 2 – 3 ). Mice did not exhibit any changes in body weight over the course of the study (Fig. 5 d). These results thus suggest that treatment with a cocktail of pAbs targeting distinct tumor-specific MSPs can afford therapeutic benefits in TNBC tumor-bearing mice while maintaining an acceptable safety profile. Table 2 Tumor growth summary statistics for the data shown in Fig. 5 B. Tukey's multiple comparisons test (DPI 10) Mean Diff. 95.00% CI of diff. Adjusted P Value Untreated Control vs 9-Ab Cocktail + PD1i 984.7 461.1 to 1508 < 0.0001 PD1i alone vs 9-Ab Cocktail + PD1i 635.3 111.7 to 1159 0.0105 nIgG + PD1i vs 9-Ab Cocktail + PD1i 651.6 128.0 to 1175 0.0082 NOTE: Data were compared on day 10 via two-way ANOVA with Tukey’s multiple comparison test. Table 3 Mouse survival summary statistics for the data shown in Fig. 5 C. Log-rank (Mantel-Cox) test Curve comparisons Chi square df P value Median survival Survival ratio Hazard ratio 95% CI for Hazard Ratio All curves 14.95 3 0.0019 Untreated vs 9-Ab CT + PD1i 10.43 1 0.0012 11.5 vs 19.0 1.652 5.340 1.231 to 23.16 PD1i vs 9-Ab CT + PD1i 12.02 1 0.0005 14.0 vs 19.0 1.357 6.382 1.378 to 29.56 nIgG + PD1i vs 9-Ab CT + PD1i 6.60 1 0.0102 13.5 vs 19.0 1.407 4.337 1.063 to 17.69 NOTE: Data were compared with log-rank (Mantel-Cox) tests. TNBC patients are promising candidates for MSP-targeted oligoclonal antibody treatment To inform the feasibility of applying an antibody cocktail-based approach to the treatment of human breast cancer, we explored the breast cancer neoepitope space using mutational data from The Cancer Genome Atlas (TCGA), comparing matched tumor and normal blood samples from TNBC (n = 100) and other breast cancer (n = 83) patients. Missense mutations within protein-coding genes comprised the majority of detected mutations for both TNBC and other breast cancers (84% and 82%, respectively), with slight variations in overall mutation type distributions between these two groups of patients (Fig. 6 ). The numbers of mutated surface neoepitopes for these 183 patients were calculated, revealing 16,758 unique missense mutations. The median numbers of MSPs in patients with TNBC and other forms of breast cancer patients were 13.5 and 8, respectively, with a much broader spread in the distribution of mutated membrane neoepitope counts for TNBC patients relative to those with other types of breast cancer (Fig. 7 a-c). Our preclinical animal data shown previously demonstrated that targeting 9 or 10 MSPs were sufficient to achieve high levels of antibody binding to tumors and effectively inhibit tumor growth ( 18 , 25 ). Guided by these preliminary data and using a cut-off of 10 MSPs per tumor, we found that a significantly higher proportion of TNBC patients harbored sufficient MSPs (> 10) to be good candidates to produce a cocktail of MSP-targeting antibodies relative to non-TNBC patients (69% vs. 42%) (Fig. 7 d). Despite the lack of conventional therapeutic targets in TNBC and associated treatment difficulties, our results suggest that the neoepitope space for this subtype of breast cancer may be even more expansive than that for other breast cancers. Strikingly, despite the high number of MSPs detected in this cohort of breast cancer patients, we found that the associated missense mutations tended to be patient-specific such that only 2.4% of 3,106 total MSP mutations were shared with two or more TNBC patients, while 97.6% were unique. Similarly, 0.2% of 3,065 MSP mutations were shared among other breast cancer patients, with the remaining 99.8% being unique (Fig. 8 ). While they are thus poor candidate targets for the mass production of tumor-engaging antibodies, these neoepitopes highlight an ideal and novel opportunity for the personalized treatment of breast cancer by administering a patient-specific cocktail of antibodies targeting a panel of tumor-associated MSPs. DISCUSSION TNBC tumors account for 10–15% of breast cancer diagnoses, and their poor responsivity to treatment and tendency towards invasive growth are associated with poor prognostic outcomes for patients with advanced disease ( 26 ). While optimal candidate targets suitable for the treatment of all TNBC cases have not been identified, the high mutational burden in these tumors provides a unique opportunity to target patient-specific tumor neoantigens using antibodies or other immunotherapies ( 27 ). In this study, we employed an optimized version of our previously reported MSP-targeting antibody cocktail strategy, leading to the successful generation of a cocktail of TNBC cell-binding pAbs with ADCC activity that successfully slowed tumor growth and prolonged survival in vivo. These promising preclinical efficacy results, coupled with our finding that approximately 69% of TNBC patients are good candidates for MSP-targeting antibody production, support the feasibility of this approach to personalized TNBC patient care. In this study, we successfully produced pAbs targeting 12 selected MSPs at a high titer. Despite high peptide affinity in initial ELISAs, 3 of these 12 pAbs showed minimal binding to EMT6 cells. Strikingly, however, the 9 remaining pAbs showed individual binding to cells and were able to bind these target tumor cells in a cumulative manner, confirming the success of our production strategy. This multi-antibody approach to tumor cell targeting may also afford therapeutic advantages. In addition to our demonstrated success in disrupting tumor growth through cocktail-based treatment strategies ( 18 , 25 ), we have also highlighted the feasibility of utilizing multiple antibodies targeting distinct antigens as an approach to superior single-tumor imaging ( 28 ). Notably, a study focused on the bispecific antibody (BsAb)-based targeting of HER2-positive tumor cells also demonstrated that the simultaneous application of two lower affinity anti-HER2 BsAbs was associated with improved overall therapeutic efficacy attributable to avidity-driven effects ( 29 ). Whether the cumulative binding of MSP-targeting antibody cocktails can provide similar avidity-based therapeutic advantages remains to be established given the distinct mechanism of action from CD3-engaging BsAbs, but holds promise as an avenue for further study, particularly given the interplay between antibody avidity, affinity, and the elicitation of ADCC and other effector functions ( 30 ). While producing neoantigen-directed therapies is inherently complex and resource-intensive given their patient specificity, other clinical studies to date have highlighted the clinical feasibility of personalized tumor vaccines or adoptive cell transfer-based approaches ( 31 ). The MSP-targeting antibody cocktail strategy is a novel approach in this therapeutic space, contributing a new tool for the arsenal of antitumor therapies. Tumor growth inhibition and prolonged survival in EMT6 tumor-bearing mice treated with MSP-targeting pAb cocktail mirrors similar successes we have achieved in murine models of melanoma and other tumors ( 18 , 25 ), providing the first direct evidence that this strategy can be applied to the treatment of TNBC. This antibody-mediated suppression of tumor growth, coupled with the strong binding of these antibodies to the surfaces of tumors but not normal tissues and their in vitro ADCC activity, is consistent with a model wherein these antibodies can coat the surfaces of MSP-expressing TNBC cells, inducing the killing of these cells by cytotoxic immune effector cell populations. While we did not characterize the precise immune cell populations that underlie this response in vivo , natural killer (NK) cells are likely to at least partially mediate this effect ( 32 ), with potential contributions from other immune cell types. Notably, we administered the antibody cocktail in combination with a PD-1 immune checkpoint inhibitor antibody, as combination treatment strategies, including PD-1/PD-L1 blockade, can more effectively sensitize the tumor microenvironment to a range of treatments ( 33 ). Combining a cocktail-based treatment strategy with other therapies, such as endocytosis inhibitors reportedly capable of sensitizing tumors to ADCC-mediated tumor cell killing ( 34 ), may afford even better therapeutic outcomes, although additional studies will be necessary to test this possibility. Strikingly, a more substantial proportion of human TNBC patients were classified as promising candidates for this MSP-targeting antibody cocktail-based treatment approach (defined by the presence of 10 + MSPs in sequenced tumor samples) as compared to patients with other forms of breast cancer (69% vs. 42%). This observation aligns well with a prior study evaluating the breast cancer neoepitope space in which TNBC was associated with the highest total mutational burden, followed by HER2 + breast tumors ( 14 ). Interestingly, that study noted that just 51% of the predicted neoepitopes were detectably expressed at the RNA level ( 14 ), which may account for the lack of observed binding activity for 3 out of 12 pAbs developed here in the EMT6 model system. These results further reinforce the importance of generating an antibody cocktail targeting a sufficient number of MSPs for each patient to maximize the odds of successfully producing multiple therapeutically active antibodies to take advantage of the heterogeneous neoantigen landscape in breast tumors ( 27 ). Future improvements to the computational approaches used to detect candidate neoepitopes and predict their expression may help refine the selection of suitable candidate MSPs to achieve higher rates of antibody binding ( 35 ), potentially translating to superior therapeutic efficacy given the observed additive binding of different MSP-targeting antibodies to tumor cells in the present study. CONCLUSIONS In summary, these results highlight the feasibility of developing and administering a cocktail of antibodies targeting TNBC-associated neoepitopes present in individual patients’ tumors to improve survival through ADCC-mediated target tumor cell killing. Considering the promise of this therapeutic approach, we have applied for and received approval from the US Food and Drug Administration (FDA) to launch a phase I clinical trial enrolling stage IV patients with TNBC and other forms of cancer to test the clinical feasibility and safety of an MSP-targeting antibody cocktail-based therapeutic pipeline (IND 171136). While more work will be essential to deploy this approach more broadly, we anticipate that the findings from this trial will form the evidentiary foundation for further optimization and expansion, providing TNBC patients with individualized therapeutic regimens that can achieve better outcomes not possible under the current standard of care. Abbreviations ADCC Antibody-dependent cellular cytotoxicity BsAb Bispecific antibody COVID-19 Coronavirus disease 2019 DAPI 4',6-diamidino-2-phenylindole DPI Days post-implantation ECD Extracellular domain ELISA Enzyme-linked immunosorbent assay EMEM Eagle's minimum essential medium ER Estrogen receptor FBS Fetal bovine serum FDA Food and Drug Administration HER2 Human epidermal growth factor receptor 2 HRP Horseradish peroxidase IACUC Institutional Animal Care and Use Committee IgG Immunoglobulin G KLH Keyhole limpet hemocyanin LDH Lactate dehydrogenase MSP Mutated cell surface proteins pAbs Polyclonal antibodies PBMC Peripheral blood mononuclear cells PD-1 Programmed cell death protein 1 PR Progesterone receptor TCGA The Cancer Genome Atlas TMB 3,3',5,5'-Tetramethylbenzidine TNBC Triple-negative breast cancer Declarations Ethics approval and consent to participate Informed consent was obtained from all individual participants included in the study following the University Vermont Institutional Review Board Regulations (Study #00000317). All animal work was completed in accordance with University of Vermont Institutional Animal Care and Use Committee (Protocol #18-002) This study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Consent for publication Not applicable. Availability of data and materials The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests SCP, GSS, YS, and DNK are shareholders of Moonshot Antibodies, Inc. All other authors have no relevant financial interests to disclose. Funding SD Ireland Cancer Research Fund and John Wayne Cancer Foundation supported this work. Imaging was performed at the Microscopy Imaging Center at the University of Vermont (RRID# SCR_018821). Bioinformatics services were provided by the Vermont Integrative Genomics Resource DNA Facility and supported the UVM Larner College of Medicine ( RRID# SCR_021775). The funding bodies had no role in the design of the study and collection, analysis, and interpretation of the data or writing the manuscript. Author Contributions SP contributed to the conceptualization, data curation, data analysis, investigation, methodology, project administration, and writing/review/editing of the manuscript. GS contributed to the conceptualization, data curation, formal analysis, investigation, methodology and preparation/review of manuscript. YS, MA, CH, RB, LM, FZ, and MF contributed to data curation, investigation, methodology and review of the manuscript. DK contributed to the conceptualization, data analysis, investigation, project administration, and writing/review/editing of the manuscript. Acknowledgements Not applicable. References Williams MJ, Werner B, Barnes CP, Graham TA, Sottoriva A. Identification of neutral tumor evolution across cancer types. Nat Genet. 2016;48(3):238-44. Hand PH, Nuti M, Colcher D, Schlom J. Definition of antigenic heterogeneity and modulation among human mammary carcinoma cell populations using monoclonal antibodies to tumor-associated antigens. Cancer Res. 1983;43(2):728-35. Basanta D, Anderson AR. Exploiting ecological principles to better understand cancer progression and treatment. Interface Focus. 2013;3(4):20130020. Marusyk A, Polyak K. Tumor heterogeneity: causes and consequences. Biochim Biophys Acta. 2010;1805(1):105-17. Greaves M, Maley CC. Clonal evolution in cancer. Nature. 2012;481(7381):306-13. Tran TXM, Jung SY, Lee EG, Cho H, Kim NY, Shim S, et al. Fear of Cancer Recurrence and Its Negative Impact on Health-Related Quality of Life in Long-term Breast Cancer Survivors. Cancer Res Treat. 2022;54(4):1065-73. Murthy RK, Loi S, Okines A, Paplomata E, Hamilton E, Hurvitz SA, et al. Tucatinib, Trastuzumab, and Capecitabine for HER2-Positive Metastatic Breast Cancer. N Engl J Med. 2020;382(7):597-609. Sledge GW, Jr., Toi M, Neven P, Sohn J, Inoue K, Pivot X, et al. The Effect of Abemaciclib Plus Fulvestrant on Overall Survival in Hormone Receptor-Positive, ERBB2-Negative Breast Cancer That Progressed on Endocrine Therapy-MONARCH 2: A Randomized Clinical Trial. JAMA Oncol. 2020;6(1):116-24. Hurvitz SA, Hegg R, Chung WP, Im SA, Jacot W, Ganju V, et al. Trastuzumab deruxtecan versus trastuzumab emtansine in patients with HER2-positive metastatic breast cancer: updated results from DESTINY-Breast03, a randomised, open-label, phase 3 trial. Lancet. 2023;401(10371):105-17. Schmid P, Cortes J, Pusztai L, McArthur H, Kümmel S, Bergh J, et al. Pembrolizumab for Early Triple-Negative Breast Cancer. N Engl J Med. 2020;382(9):810-21. Braster R, O'Toole T, van Egmond M. Myeloid cells as effector cells for monoclonal antibody therapy of cancer. Methods. 2014;65(1):28-37. Parrillo JE, Fauci AS. Apparent direct cellular cytotoxicity mediated via cytophilic antibody. Multiple Fc receptor bearing effector cell populations mediating cytophilic antibody induced cytotoxicity. Immunology. 1977;33(6):839-50. Parakh S, Gan HK, Parslow AC, Burvenich IJ, Burgess AW, Scott AM. Evolution of anti-HER2 therapies for cancer treatment. Cancer treatment reviews. 2017;59:1-21. Narang P, Chen M, Sharma AA, Anderson KS, Wilson MA. The neoepitope landscape of breast cancer: implications for immunotherapy. Bmc Cancer. 2019;19:1-10. Brennick CA, George MM, Corwin WL, Srivastava PK, Ebrahimi-Nik H. Neoepitopes as cancer immunotherapy targets: key challenges and opportunities. Immunotherapy. 2017;9(4):361-71. Joubert S, Stuible M, Lord-Dufour S, Lamoureux L, Vaillancourt F, Perret S, et al. A CHO stable pool production platform for rapid clinical development of trimeric SARS-CoV-2 spike subunit vaccine antigens. Biotechnol Bioeng. 2023;120(7):1746-61. Pero SC, Nagulapally AB, Mei L, Zhang F, Sholler GS, Krag DN, Shukla GS. Development of Clinical-Grade Antibodies against Tumor-Specific Mutations to Target Neuroblastoma. Ann Clin Lab Sci. 2022;52(3):349-58. Shukla G, Pero S, Sun Y-J, Mei L, Zhang F, Sholler G, Krag D. Multiple antibodies targeting tumor-specific mutations redirect immune cells to inhibit tumor growth and increase survival in experimental animal models. Clinical and Translational Oncology. 2020;22:1094-104. Soudy M, Anwar AM, Ahmed EA, Osama A, Ezzeldin S, Mahgoub S, Magdeldin S. UniprotR: Retrieving and visualizing protein sequence and functional information from Universal Protein Resource (UniProt knowledgebase). Journal of Proteomics. 2020;213:103613. UniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Res. 2023;51(D1):D523-d31. Team RC. R: A language and environment for statistical computing. Foundation for Statistical Computing, Vienna, Austria. 2013. Allaire J. RStudio: integrated development environment for R. Boston, MA. 2012;770(394):165-71. Rockwell SC, Kallman RF, Fajardo LF. Characteristics of a serially transplanted mouse mammary tumor and its tissue-culture-adapted derivative. Journal of the National Cancer Institute. 1972;49(3):735-49. Xiao Y, Zheng P, Xu W, Wu Z, Zhang X, Wang R, et al. Progesterone receptor impairs immune respond and down-regulates sensitivity to anti-LAG3 in breast cancer. Transl Res. 2024;271:68-78. Shukla GS, Sun Y-J, Pero SC, Krag DN. A cocktail of polyclonal affinity enriched antibodies against melanoma mutations increases binding and inhibits tumor growth. Journal of immunological methods. 2020;478:112720. Zagami P, Carey LA. Triple negative breast cancer: Pitfalls and progress. NPJ breast cancer. 2022;8(1):95. Benvenuto M, Focaccetti C, Izzi V, Masuelli L, Modesti A, Bei R, editors. Tumor antigens heterogeneity and immune response-targeting neoantigens in breast cancer. Seminars in Cancer Biology; 2021: Elsevier. Sun Y, Shukla G, Pero SC, Currier E, Sholler G, Krag D. Single tumor imaging with multiple antibodies targeting different antigens. Biotechniques. 2012;52(4). Slaga D, Ellerman D, Lombana TN, Vij R, Li J, Hristopoulos M, et al. Avidity-based binding to HER2 results in selective killing of HER2-overexpressing cells by anti-HER2/CD3. Science translational medicine. 2018;10(463):eaat5775. Oostindie SC, Lazar GA, Schuurman J, Parren PW. Avidity in antibody effector functions and biotherapeutic drug design. Nature Reviews Drug Discovery. 2022;21(10):715-35. Lybaert L, Thielemans K, Feldman SA, van der Burg SH, Bogaert C, Ott PA. Neoantigen-directed therapeutics in the clinic: where are we? Trends in cancer. 2023;9(6):503-19. Dixon KJ, Wu J, Walcheck B. Engineering anti-tumor monoclonal antibodies and Fc receptors to enhance ADCC by human NK cells. Cancers. 2021;13(2):312. Yi M, Zheng X, Niu M, Zhu S, Ge H, Wu K. Combination strategies with PD-1/PD-L1 blockade: current advances and future directions. Molecular cancer. 2022;21(1):28. Chew HY, De Lima PO, Cruz JLG, Banushi B, Echejoh G, Hu L, et al. Endocytosis inhibition in humans to improve responses to ADCC-mediating antibodies. Cell. 2020;180(5):895-914. e27. Rocha LGdN, Guimarães PAS, Carvalho MGR, Ruiz JC. Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies. Vaccines. 2024;12(8):836. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6073571","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":422141205,"identity":"a5eb95c6-db51-49db-a7b1-460675f6ec7c","order_by":0,"name":"Stephanie C. Pero","email":"","orcid":"","institution":"University of Vermont Larner College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Stephanie","middleName":"C.","lastName":"Pero","suffix":""},{"id":422141206,"identity":"cc901204-2e3b-43c4-96e5-92d031f39f32","order_by":1,"name":"Girja S. Shukla","email":"","orcid":"","institution":"University of Vermont Larner College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Girja","middleName":"S.","lastName":"Shukla","suffix":""},{"id":422141207,"identity":"abc7bd2d-f0cb-482e-998e-5e0b75ee0901","order_by":2,"name":"Yujing Sun","email":"","orcid":"","institution":"University of Vermont Larner College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yujing","middleName":"","lastName":"Sun","suffix":""},{"id":422141208,"identity":"66dada3e-c164-446d-af73-7e06217e3176","order_by":3,"name":"Ramiro Barrantes-Reynolds","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Ramiro","middleName":"","lastName":"Barrantes-Reynolds","suffix":""},{"id":422141209,"identity":"78c60346-ac98-4b5f-b0fb-c34c12e9aed7","order_by":4,"name":"Colin J. Hartman","email":"","orcid":"","institution":"Dartmouth College Thayer School of Engineering","correspondingAuthor":false,"prefix":"","firstName":"Colin","middleName":"J.","lastName":"Hartman","suffix":""},{"id":422141210,"identity":"489bb1c5-f8f0-4a46-b23b-e359d92195d1","order_by":5,"name":"Margaret E. Ackerman","email":"","orcid":"","institution":"Dartmouth College Thayer School of Engineering","correspondingAuthor":false,"prefix":"","firstName":"Margaret","middleName":"E.","lastName":"Ackerman","suffix":""},{"id":422141211,"identity":"3b3e70e4-4052-4124-9d1f-99e10a3a92ba","order_by":6,"name":"Linda Mei","email":"","orcid":"","institution":"University of Vermont Larner College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Linda","middleName":"","lastName":"Mei","suffix":""},{"id":422141212,"identity":"a2829893-db11-4205-b104-4e535722b203","order_by":7,"name":"Fan Zhang","email":"","orcid":"","institution":"University of Vermont","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Zhang","suffix":""},{"id":422141213,"identity":"0bbbb585-8f44-46bf-a195-84093997cb66","order_by":8,"name":"Matthew R. Fournier","email":"","orcid":"","institution":"University of Vermont Larner College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"R.","lastName":"Fournier","suffix":""},{"id":422141214,"identity":"e7f93034-2584-4246-8a54-cf467ea461a5","order_by":9,"name":"David N. Krag","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYDCCA0DEw5AAZDEDmWxQUR7itLAlEK+FAaKFx4A4LXzHzxgeeMOQls/fv+brhg9lDIkbrh1gfPC2DbcWyTM5BgfnMORYzrjxdtvNGeeAWm4nMBvOxaPF4EBawmEehgoDhhtnt93mbWNInDk7gU2aF5+W888gWuRvnHl2+y9EC/tvvFpuJB8AaskxMDjfw3abEailXzqBjRmfFskbjw8cnGOQZmB4g83sZs85CeN+6cRmyTnncGvhO5/Y/OFNRbKB3PnDz278KLORbZNOPvjhTRluLVDnAbFEAoglAcSMDYTUQwH/ASIVjoJRMApGwYgDAG3kWsZW/YYEAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-5355-5999","institution":"University of Vermont Larner College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"David","middleName":"N.","lastName":"Krag","suffix":""}],"badges":[],"createdAt":"2025-02-20 16:24:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6073571/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6073571/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78139629,"identity":"b8c79165-81ba-4607-a203-7876a0343023","added_by":"auto","created_at":"2025-03-10 09:54:43","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":124164,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCharacterization of antibodies targeting EMT6 tumor-associated mutated surface proteins\u003c/strong\u003e.\u003cstrong\u003e \u003c/strong\u003eELISA binding curves of serially diluted (2-fold) samples of 12 pAbs antibodies to the corresponding mutated peptide. Absorbance values represent average values from duplicate wells.\u003c/p\u003e","description":"","filename":"Binder11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/dadb982c5625c50f61f6853d.jpg"},{"id":78142525,"identity":"fa00a08e-f3ff-4c03-a037-fb16f9ccdb52","added_by":"auto","created_at":"2025-03-10 10:26:44","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":483410,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCell binding profiles of EMT6 tumor-associated MSP-specific pAbs. (a) \u003c/strong\u003eImmunofluorescent images showing antibody binding to individual MSPs on EMT6 cancer cells (smaller images) and cumulative antibody binding to all 9 MSPs (the larger leftmost image). These results demonstrate variable antibody binding to individual MSPs and strong antibody binding of a cocktail of antibodies targeting all 9 MSPs. The abbreviated name of each targeted mutated protein is inset.\u003cstrong\u003e \u003c/strong\u003eNo binding to EMT6 cells was observed with control rabbit IgG. \u003cstrong\u003e(b) \u003c/strong\u003eImmunofluorescent images showing antibody binding to an increasing number of MSPs on EMT6 cancer cells. The leftmost image shows antibody binding to 1 MSP. Each image moving to the right corresponds to treatment with one additional antibody targeting a distinct MSP. The rightmost image shows strong antibody binding when targeting all 9 MSPs.\u003c/p\u003e","description":"","filename":"Binder12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/3cbf32559742100a841a26ac.jpg"},{"id":78139870,"identity":"2482d8ef-9719-4d74-9bf7-6159baf76d9c","added_by":"auto","created_at":"2025-03-10 10:02:44","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":516622,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of the specificity of MSP-targeting pAb cocktail binding to EMT6 cells and normal mouse tissues\u003c/strong\u003e. Histologic sections of EMT6 and normal tissues were stained with 2.25 µg of the pAb cocktail targeting 9 MSPs (0.25 µg/Ab) or control rabbit IgG (rIgG, 2.25 µg) as a negative control. Secondary AlexaFluor 568 goat-anti-rabbit IgG (H+L) was used to detect pAb binding (Red, top row), while nuclei were counterstained with DAPI (blue, bottom row).\u003c/p\u003e","description":"","filename":"Binder13.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/6a06f9fc380b7f198475432e.jpg"},{"id":78140909,"identity":"80aa86bf-8ed9-4356-bd5e-1a96f5342b7a","added_by":"auto","created_at":"2025-03-10 10:10:44","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":120341,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAn antibody cocktail targeting nine EMT6 MSPs exhibits strong cytotoxicity in an \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e ADCC assay. \u003c/strong\u003eThe assay was performed across a range of PBMC:EMT6 ratios. Cells were treated with 1 µg of the 9-pAb cocktail or control rabbit IgG or were left untreated. Barplots of the mean ± SD (n=3). Comparisons were made with one-way ANOVAs and Tukey’s post hoc test. ***P\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Binder14.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/cd83bddc1d69ed1de09f5073.jpg"},{"id":78139636,"identity":"7c4b55bb-c774-450d-be46-7593cde5ec3e","added_by":"auto","created_at":"2025-03-10 09:54:44","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":214138,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEMT6 tumor growth inhibition and survival are enhanced in mice treated with a customized cocktail of MSP-targeting antibodies. (a)\u003c/strong\u003e Overview of the timing of implantation and treatment with a 9-Ab antibody cocktail and anti-PD-1 in BALB/c mice implanted subcutaneously with 1x10\u003csup\u003e6\u003c/sup\u003e EMT6 cells. \u003cstrong\u003e(b)\u003c/strong\u003e Tumor growth as measured daily over the course of the study. \u003cstrong\u003e(c)\u003c/strong\u003e Murine survival over the course of the study. \u003cstrong\u003e(d)\u003c/strong\u003e Murine body weight over the course of the study. DPI: days post-implantation, PD1i: PD-1 inhibitor, nIgG: normal rabbit control IgG, 9-Ab CT: cocktail of 9 antibodies targeting neoepitopes of 9 mutated cell surface proteins. Data are means ± SEM for 6 mice per group. Tumor growth data were compared via two-way ANOVA. *9-pAb CT+PD1i group is significantly different from Untreated (P\u0026lt;0.0001), PD1i alone (P=0.0105) and nIgG+PD1i (P=0.0082) groups.\u003c/p\u003e","description":"","filename":"Binder15.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/e06e89261675f17b462f0de3.jpg"},{"id":78139631,"identity":"978d6df8-5b9e-43ce-ac52-2c5e1f879ff0","added_by":"auto","created_at":"2025-03-10 09:54:44","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":147901,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe distribution of mutation variant types in human breast cancer. (a) \u003c/strong\u003e100 triple-negative breast cancer patients and \u003cstrong\u003e(b)\u003c/strong\u003e 83 other breast cancer patients in the TCGA dataset were analyzed. \u0026nbsp;Data are means ± SDand show the numbers of missense, nonsense, frameshift deletions, frameshift insertions, and other mutations. Other mutations include in-frame deletions, non-stop, splice-site, translation-start, and in-frame insertion mutations.\u003c/p\u003e","description":"","filename":"Binder16.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/353c5f616b9775b713d8e1b6.jpg"},{"id":78139874,"identity":"d75340d0-92d2-4bd7-9118-bc50a7d7ea8f","added_by":"auto","created_at":"2025-03-10 10:02:44","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":286471,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMutation distributions in TNBC and non-TNBC patients from the TCGA database. (a)\u003c/strong\u003e The distribution of MSPs in each patient analyzed in the TCGA dataset. \u003cstrong\u003e(b, c)\u003c/strong\u003e The number of (b) missense mutations and (c) MSPs in TNBC patients and other breast cancer patients using a box and whisker plot. \u003cstrong\u003e(d)\u003c/strong\u003e The percentages of patients eligible for oligoclonal antibody production, with eligibility being defined by the presence of \u0026gt;10 membrane neoepitopes. Results were analyzed with χ\u003csup\u003e2 \u003c/sup\u003etests. ***P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Binder17.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/fa1064619c3f7f22351baa1d.jpg"},{"id":78141347,"identity":"ead75834-8f53-45ad-af88-3ad8dd6c8303","added_by":"auto","created_at":"2025-03-10 10:18:44","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":103064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMembrane-associated missense mutation profiles in breast cancer patients are largely patient-specific.\u003c/strong\u003eUnique and shared mutation frequencies among\u003cstrong\u003e (a) \u003c/strong\u003e100 TNBC patients \u003cstrong\u003e(b)\u003c/strong\u003e83 non-TNBC patients were analyzed for the fraction of MSP epitopes that are unique to one patient (Blue) and the fraction of shared by two or more patients (Red).\u003c/p\u003e","description":"","filename":"Binder18.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/8a6bd211545f67fbdcaf6158.jpg"},{"id":81732394,"identity":"2c5503d3-daf9-44c3-9818-975ffa1640e3","added_by":"auto","created_at":"2025-04-30 19:35:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3243546,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6073571/v1/05612c4f-61ff-44d0-8433-bdde0dceaa9b.pdf"}],"financialInterests":"","formattedTitle":"Novel antibody cocktail therapy targeting extracellular tumor-specific mutations to treat triple-negative breast cancer","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eTumor growth entails the acquisition of additional mutations and the consequent emergence of increasingly heterogeneous cell populations (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Even when available treatments achieve a clinical complete response, the expansion of small populations of treatment-resistant tumor cells often leads to recurrence and drug resistance following successful treatment (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), which is a persistent challenge to effective breast cancer management (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). While recent combination regimens have conferred survival advantages to subsets of breast cancer patients with recurrent disease (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), they have not fully resolved the underlying challenge of drug resistance. This is a particularly pressing clinical challenge for patients with triple-negative breast cancer (TNBC) for whom fewer treatment options are available. In the neoadjuvant setting, patients with TNBC exhibit a higher rate of complete response with the addition of checkpoint inhibitors, but incomplete tumor eradication remains a problem (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Targeted immune therapies, including monoclonal antibodies, vaccines, and T-cell therapies, must therefore be capable of overcoming tumor heterogeneity to contribute to better patient outcomes.\u003c/p\u003e \u003cp\u003eWe have focused on addressing the challenge of intratumoral heterogeneity by leveraging the firmly established ability of immune effector cells to clear antibody-opsonized target cells (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). TNBC patients lack any universal surface markers that can be safely and effectively targeted with therapeutic antibodies in a manner akin to the trastuzumab-based treatment of HER2\u0026thinsp;+\u0026thinsp;breast cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). However, TNBC is characterized by a higher mutational burden than other forms of breast cancer (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), with elevated rates of random genomic mutation contributing to the generation of immunologically novel protein epitopes (here referred to as neoepitopes) expressed in tumors but not normal tissues. These neoepitopes are ideal targets for a range of therapeutic interventions, including tumor vaccines, adoptive T cell therapy, and antibody-based treatment (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), as they are tumor cell-specific. We refer to the cell surface proteins harboring these neoepitopes as \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003em\u003c/span\u003eutated cell \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003es\u003c/span\u003eurface \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ep\u003c/span\u003eroteins (MSPs). As opposed to \u0026ldquo;driver\u0026rdquo; mutations, these MSPs are generated in a largely random manner, they are almost all patient-specific, with overlap among patients being largely attributable to chance. Effective antibody-based neoepitope targeting therefore relies on the production of these antibodies for each patient individually. While this personalized approach may once have been considered infeasible, the COVID-19 pandemic accelerated the development of methods suitable for more rapidly producing therapeutic antibodies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). We have leveraged and further optimized these techniques to establish a pipeline for the rapid identification of suitable tumor-specific MSP targets and the small-batch production of custom cocktails of antibodies targeting multiple MSPs for individual patients (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). This approach takes advantage of the heterogeneity inherent within tumors by directing immune cells to clear tumor cells bearing myriad distinct surface neoepitopes. We have been able to successfully prolong the survival of tumor-bearing mice by administering tumor-specific cocktails of MSP-targeting antibodies, without any adverse normal tissue pathology (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, the feasibility of using this individualized approach to treat TNBC has not been assessed to date.\u003c/p\u003e \u003cp\u003eGiven the lack of consistent target availability among TNBC patients and high rates of tumor recurrence attributable to the heterogeneity of tumor cell subpopulations, in this study we sought to exploit the neoepitope space conferred by such heterogeneity to investigate the feasibility of treating TNBC using MSP-targeting antibodies using the EMT6 TNBC mouse model. We also surveyed sequencing data from breast cancer patients to highlight the potential amenability of human TNBC to this MSP-targeting antibody treatment strategy, underscoring its promise as a novel individualized approach with the potential to prolong survival and quality of life for patients who currently lack reliable therapeutic options.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCells and Reagents\u003c/h2\u003e \u003cp\u003eEMT6/P cells (Sigma-Aldrich) were cultured according to the manufacturer\u0026rsquo;s instructions in EMEM containing 10% fetal bovine serum (FBS; Sigma), 2 mM glutamine, 1% non-essential amino acids (Sigma), and penicillin/streptomycin (Sigma). Goat serum was obtained from Jackson Immunoresearch. Antibodies used for this study included anti-mouse PD-1 (CD279; clone RMP1-14; Bio X cell), rabbit IgG, goat anti-rabbit IgG (H\u0026thinsp;+\u0026thinsp;L) cross-adsorbed secondary antibody Alexa Fluor\u0026reg; 568 conjugate (Invitrogen), and anti-Rabbit IgG Fc Monoclonal Secondary Antibody HRP conjugate (GenScript). Other reagents included paraformaldehyde (16% solution, EM Science, USA), DAPI (Invitrogen), fluorescent mounting medium (DAKO), Casein-TBS blocker (Pierce), soluble 3,3',5,5'-Tetramethylbenzidine (TMB; EMD Millipore), low-IgG FBS (Gibco). All other chemicals were of the highest quality grade and obtained from commercial sources.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMissense Mutation Localization\u003c/h3\u003e\n\u003cp\u003eWhole exome sequencing and variant data for the EMT6/P cell line were received from Charles River Laboratories. The human patient somatic mutation information and variant calls were obtained from the open access collection of The Cancer Genome Atlas Project (TCGA; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cancer.gov/tcga\u003c/span\u003e\u003cspan address=\"https://www.cancer.gov/tcga\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with available matching tumor and normal blood data. To identify the subcellular localization of each missense mutation, the UniProtID mapping service was used (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). First, the correct UniProtID for each gene was identified to ensure the correct isoform was considered. Entries with no UniProtID were eliminated as data on subcellular localization could not be obtained. For each UniProtID, annotated subcellular location information was obtained from Uniprot using the uniprotR package (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/UniprotR/citation.html\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/UniprotR/citation.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Given the variant position in the gene, the exact subcellular location of the variant was identified, including whether the variant was in the extracellular domain or located on a secreted protein. Programming was performed using the R programming language (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and reports were generated using RStudio (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMissense mutation-related information was extracted from the TCGA database, including Estrogen Receptor (ER)/Progesterone Receptor (PR) / human epidermal growth factor receptor 2 (HER2) status, HUGO gene symbol, position in the chromosome, and precise variant information. Our patient dataset included 100 TNBC patients (ER\u003csup\u003e\u0026minus;\u003c/sup\u003e/PR\u003csup\u003e\u0026minus;\u003c/sup\u003e/HER2\u003csup\u003e\u0026minus;\u003c/sup\u003e) and 83 other breast cancer patients, providing a broad spectrum of genetic information for analysis.\u003c/p\u003e \u003cp\u003eThe number of MSP neoepitopes for each patient was calculated by adding together the following: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) the number of mutations identified in protein extracellular domains, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) the number of mutations identified within secreted proteins, and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) 50% of the mutations located in cell surface-associated proteins for which an exact location was not defined. Cell surface-associated proteins were defined as those proteins associated with terms in the UniProt database including apical cell membrane, cell membrane, multi- and single-pass membrane protein, and peripheral membrane proteins. The 50% hit rate for membrane proteins without a defined extracellular domain was determined based on the percent favorable (extracellular domain or secreted) mutations on defined extracellular proteins.\u003c/p\u003e\n\u003ch3\u003ePeptide Synthesis\u003c/h3\u003e\n\u003cp\u003ePeptides (11\u0026ndash;14 amino acids) including target mutated residues and adjacent amino acids that were predicted to be immunogenic in rabbits were designed by GenScript (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Peptides were synthesized to have an N- or C-terminal cysteine for conjugation to keyhole limpet hemocyanin (KLH). Before conjugation, each peptide was purified using high-performance liquid chromatography at \u0026gt;\u0026thinsp;95% purity, and mass spectrometry was performed to confirm sequence identity. Unconjugated peptides were used for ELISA analysis. KLH-conjugated peptides were used for rabbit immunization for antibody production.\u003c/p\u003e\n\u003ch3\u003eAntibody Production and Characterization\u003c/h3\u003e\n\u003cp\u003ePurified antibody production and ELISA-based characterization were performed using methods previously reported (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Immunization of 2 rabbits per peptide using the polyexpress protocol by Genscript. Antibodies were purified by affinity purification with the peptide immunogen. Final antibodies were dissolved in PBS with no additives. For ELISAs, the rabbit pAbs capable of binding to mutated peptide-coated wells (4 \u0026micro;g/ml) were detected using HRP-conjugated anti-rabbit IgG Fc (Genscript) and soluble TMB, measuring absorbance at 650 nm (A\u003csub\u003e650\u003c/sub\u003e).\u003c/p\u003e\n\u003ch3\u003eAntibody-Dependent Cellular Cytotoxicity (ADCC) Assay\u003c/h3\u003e\n\u003cp\u003eEMT6/P cells (20,000 cells/well) were seeded in a U-bottom 96-well plate (Falcon) in media containing low-IgG FBS. Peripheral blood mononuclear cells (PBMCs) were isolated from freshly collected healthy human donor blood (UVM IRB approved protocol #0000317) using Accuspin tubes with Histopaque-1077 (Sigma), according to the manufacturer\u0026rsquo;s instructions. PBMCs (effector cells) were resuspended in serum-free CTL-Test medium (Cellular Technology Limited) with freshly added L-glutamine (2 mM, Gibco). PBMCs were added to target cells at varying ratios. Each well was treated with the 9 pAb-cocktail (1 \u0026micro;g total, mixing antibodies in equal amounts), control rabbit polyclonal IgG (1 \u0026micro;g), or no antibody, in triplicate. The cells were placed at 37\u0026deg;C in a 5% CO\u003csub\u003e2\u003c/sub\u003e humidified incubator for 21 h. ADCC was assessed using the LDH-Glo Cytotoxicity Assay Kit (Promega) according to the manufacturer\u0026rsquo;s instructions. Plates were analyzed using a microplate luminometer (Turner Biosystems). EMT6/P control wells were treated with 2 \u0026micro;L of 10% Triton X‐100 for 30 min to lyse the cells as the maximum release control wells. Percent cytotoxicity was calculated as follows: [(Experimental \u0026ndash; Effector Spontaneous \u0026ndash; Target Spontaneous)/(Target Maximum \u0026ndash; Target Spontaneous)] \u0026times; 100.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnimal Care\u003c/h2\u003e \u003cp\u003e Animal procedures used in this study were approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Vermont (Protocol # 18\u0026thinsp;\u0026minus;\u0026thinsp;002). The syngeneic EMT6 tumor model used for this study was derived from the propagation of hyperplastic alveolar nodules transplanted in BALB/c mice (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). This tumor epithelial cell line shows characteristics of triple-negative breast tumors. Female BALB/c (6\u0026ndash;7 weeks old) were obtained from the Jackson Laboratory (Bar Harbor, ME, USA). Mice were kept in an animal facility with standard ventilation and lighting (12-hour light/dark cycles), and free access to food pellets and water. Mice were allowed to acclimate for one week, after which they were numbered, and their right flank was shaved for tumor implantation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAnimal Treatments\u003c/h3\u003e\n\u003cp\u003eAn initial experiment was performed to determine the optimal number of EMT6/P tumor cells inoculation for producing a tumor with a\u0026thinsp;~\u0026thinsp;2000 mm\u003csup\u003e3\u003c/sup\u003e volume in 15\u0026ndash;20 days. EMT6/P cells were grown in standard culture medium until ~\u0026thinsp;70% confluent, at which time they were harvested, washed with PBS, and suspended in PBS at the desired concentration. We subcutaneously injected 3 groups (n\u0026thinsp;=\u0026thinsp;5) of BALB/c mice with 0.5 x 10\u003csup\u003e6\u003c/sup\u003e, 1 x 10\u003csup\u003e6\u003c/sup\u003e, or 1.5 x 10\u003csup\u003e6\u003c/sup\u003e EMT6/P breast tumor cells suspended in 0.1 mL of PBS.\u003c/p\u003e \u003cp\u003eIn the subsequent experiment, the effect of treatment with a cocktail of rabbit pAbs directed against mutated peptides on EMT6/P tumor growth and murine survival was assessed. In total, 24 BALB/c mice were subcutaneously implanted with 1 x 10\u003csup\u003e6\u003c/sup\u003e tumor cells in the shaved right flank. These tumor-implanted mice were then randomized into four groups (n\u0026thinsp;=\u0026thinsp;6/group) and treated as follows:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eGroup 1. No treatment\u003c/p\u003e\u003cp\u003eGroup 2. PD1i only: Mice were each intraperitoneally injected with 0.2 mg of rat anti-mouse PD-1 (CD279; clone RMP1-14) at 3, 5, 7, 9, and 11 days post-implantation (DPI).\u003c/p\u003e\u003cp\u003eGroup 3. Rabbit polyclonal IgG\u0026thinsp;+\u0026thinsp;PD1i: Mice were each subcutaneously injected with 0.2 mg at the tumor base of normal rabbit IgG at 3, 4, 5, 6, and 7 DPI, and were intraperitoneally injected with 0.2 mg of rat anti-mouse PD-1 (CD279; clone RMP1-14) at 3, 5, 7, 9, and 11 DPI.\u003c/p\u003e\u003cp\u003eGroup 4. pAb Cocktail\u0026thinsp;+\u0026thinsp;PD1i: Mice were each subcutaneously injected at the tumor base with 0.2 mg of a cocktail of 9 pAb directed against mutated peptides at 3, 4, 5, 6, and 7 DPI, and were intraperitoneally injected with 0.2 mg of rat anti-mouse PD-1 (CD279; clone RMP1-14) at 3, 5, 7, 9, and 11 DPI.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eTumor Growth and Animal Survival\u003c/h3\u003e\n\u003cp\u003eElectronic calipers were used to track tumor growth daily beginning at 7 DPI, and the tumor volume was calculated as follows: V = (W\u003csup\u003e2\u003c/sup\u003e \u0026times; L)/2, where V, W, and L respectively denote the tumor volume, width, and length. Survival time was recorded based on animal death or humane endpoints (tumor volume\u0026thinsp;\u0026ge;\u0026thinsp;2000 mm\u003csup\u003e3\u003c/sup\u003e, or symptoms of physical distress such as dehydration, difficulty walking, cachexia, or other symptoms) per an established IACUC protocol. The body weights of tumor-bearing mice were measured twice weekly to track their overall health.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence Microscopy\u003c/h2\u003e \u003cp\u003eEMT6/P tumors were harvested from BALB/c mice, while normal tissues (lung, liver, brain, heart, kidney, and spleen) were harvested from untreated BALB/c mice. Harvested tissues were snap-frozen, stored at -80\u0026deg;C, and sectioned (5 \u0026micro;m) on glass slides for staining. Cell and tissue staining were performed as reported previously (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Alexa Fluor 568 goat-anti-rabbit IgG (H\u0026thinsp;+\u0026thinsp;L) (Invitrogen) was used to detect targeted rabbit antibody binding.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eTumor growth was compared among animals in different treatment groups with two-way ANOVA and Tukey's multiple comparison test. Kaplan-Meier plots and log-rank (Mantel-Cox) tests were used to compare survival differences among groups. The 95% confidence intervals (CIs) for median survival and corresponding hazard ratios were estimated. GraphPad Prism (San Diego, CA, USA) was used for data analysis and figure preparation. Further details regarding experimental tests and replicates are described in figure legends.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEMT6 tumor cells express surface neoepitopes suitable for antibody-based targeting\u003c/h2\u003e \u003cp\u003eTo assess the preclinical feasibility of using a cocktail of oligoclonal MSP-targeting antibodies to treat TNBC \u003cem\u003ein vivo\u003c/em\u003e, we selected the murine EMT6 cell line as it is a syngeneic immunocompetent model that has been extensively used in previous TNBC studies (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). When we conducted a mutational analysis of EMT6 cells, we identified 1,252 total somatic missense mutations, of which 104 were located within regions encoding the extracellular domains (ECDs) of membrane proteins. These 104 mutations were present across 92 genes harboring a single mutation, as well as 6 genes harboring two mutations each (\u003cem\u003eFolh1, Grid2, Grik1, Lepr, Ptprb\u003c/em\u003e, and \u003cem\u003eSort1\u003c/em\u003e) in EMT6 cells. The identified mutations included known cancer driver mutations in 5 ECD targets and 1 secreted protein.\u003c/p\u003e \u003cp\u003eWe generated pAbs targeting 12 different MSPs in EMT6 cells using a mutated peptide vaccination approach based on these identified somatic missense mutations. Following vaccination with peptides containing the appropriate amino acid substitution corresponding to each mutation, antibodies directed against each MSP neoepitope were affinity-enriched from the serum of vaccinated rabbits. We successfully prepared high-titer antibodies specific for all 12 targets with \u0026ge;\u0026thinsp;95% purity and strong binding affinity for their cognate antigens (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). When tested for binding to the surface of EMT6 cells, 9 of the 12 pAbs exhibited positive binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Strikingly, when these antibodies were combined, a progressive increase in fluorescent signal was observed on the surface of EMT6 cells as the number of pAbs targeting different MSPs increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). In contrast, even at the highest concentration tested, the polyclonal IgG from control rabbits failed to yield a significant immunofluorescent signal compared to the pAbs.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of prepared pAbs targeting 12 EMT6 tumor-associated MSPs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtein Name_Mutation site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMutated Peptide Vaccine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePurity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTiter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEC50 (M)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDcbld2_N416K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYHKDVRN\u003cb\u003eK\u003c/b\u003eFLPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.18E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFolh1_S550T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWKTNKVS\u003cb\u003eT\u003c/b\u003eYPLC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.76E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMfsd14b_N320T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCKLMRSLG\u003cb\u003eT\u003c/b\u003eKNT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.62E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMep1b_F242L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVIGQRMD\u003cb\u003eL\u003c/b\u003eSDYDC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.57E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrik1_T548P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCLYRKPNG\u003cb\u003eP\u003c/b\u003eNPG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDscam_S212R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCGETRQSN\u003cb\u003eR\u003c/b\u003eARL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.68E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePcdha7_A381G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVFDRDSG\u003cb\u003eG\u003c/b\u003eNGQC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.84E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCdh20_A534P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCYSL\u003cb\u003eP\u003c/b\u003ePEAANNP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.01E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSort1_R434W\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQGG\u003cb\u003eW\u003c/b\u003eWEHLRKPENC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.71E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTarm1_E77D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSVKPYNLT\u003cb\u003eD\u003c/b\u003eETAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMmp14_P316S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePKNPAYG\u003cb\u003eS\u003c/b\u003eNIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.24E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIl1rl2_P62A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYKT\u003cb\u003eA\u003c/b\u003eSKSPVSNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;1:512000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.59E-11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNOTE: Mutated amino acids are highlighted in boldface text.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMSP-targeting antibody cocktail treatment kills target tumor cells and prolongs survival\u003c/h2\u003e \u003cp\u003eTo evaluate the specificity of a cocktail prepared from these 9 pAbs, they were next used for the immunofluorescent staining of EMT6 tumors or healthy major organs from BALB/c mice. While the 9-pAb cocktail exhibited strong binding to EMT6 tumors, no binding above background levels was noted for healthy lungs, brain, heart, liver, spleen, or kidneys (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), confirming the tumor-specific binding of these MSP-targeting antibodies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo examine the ability of this 9-pAb cocktail to mediate target tumor cell killing, an antibody-dependent cellular cytotoxicity (ADCC) assay was performed in which EMT6 cells were co-cultured with healthy donor peripheral blood mononuclear cells (PBMCs) at a range of PBMC: target cell ratios (100:1, 50:1, 25:1) in the presence of 9-pAb cocktail or control polyclonal IgG. Cytotoxicity was then analyzed after 21 h using a lactate dehydrogenase (LDH) release assay, revealing that the 9-pAb cocktail was able to induce high levels of EMT6 cell death, including\u0026thinsp;\u0026gt;\u0026thinsp;80% death at a 100:1 PBMC: target cell ratio (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eGiven its preferential tumor-specific binding and ability to readily facilitate ADCC-dependent EMT6 tumor cell killing, we tested the ability of the 9-pAb cocktail to prevent EMT6 tumor growth \u003cem\u003ein vivo\u003c/em\u003e. To that end, BALB/c mice were subcutaneously implanted in the right flank with 1x10\u003csup\u003e6\u003c/sup\u003e EMT6 cells. Beginning 3 days post-implantation, mice were subcutaneously injected with the 9-pAb cocktail or control polyclonal IgG (0.2 mg/day) at the tumor base daily for 5 days. In addition, 0.2 mg of rat anti-mouse PD-1 was intraperitoneally injected into these mice on days 3, 5, 7, 9, and 11 after tumor implantation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). In this experiment, combined 9-pAb cocktail and anti-PD-1 treatment was associated with significantly reduced tumor growth and significantly prolonged murine survival (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, c and Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Mice did not exhibit any changes in body weight over the course of the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). These results thus suggest that treatment with a cocktail of pAbs targeting distinct tumor-specific MSPs can afford therapeutic benefits in TNBC tumor-bearing mice while maintaining an acceptable safety profile.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTumor growth summary statistics for the data shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTukey's multiple comparisons test (DPI 10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean Diff.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e95.00% CI of diff.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted P Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUntreated Control vs 9-Ab Cocktail\u0026thinsp;+\u0026thinsp;PD1i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e984.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e461.1 to 1508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD1i alone vs 9-Ab Cocktail\u0026thinsp;+\u0026thinsp;PD1i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e635.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111.7 to 1159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.0105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enIgG\u0026thinsp;+\u0026thinsp;PD1i vs 9-Ab Cocktail\u0026thinsp;+\u0026thinsp;PD1i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e651.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128.0 to 1175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.0082\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNOTE: Data were compared on day 10 via two-way ANOVA with Tukey\u0026rsquo;s multiple comparison test.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMouse survival summary statistics for the data shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eLog-rank (Mantel-Cox) test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurve comparisons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChi square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian survival\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSurvival ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHazard ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI \u003c/p\u003e \u003cp\u003efor Hazard Ratio\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll curves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUntreated vs 9-Ab CT\u0026thinsp;+\u0026thinsp;PD1i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.5 vs 19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.231 to 23.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD1i vs 9-Ab CT\u0026thinsp;+\u0026thinsp;PD1i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.0 vs 19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.378 to 29.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003enIgG\u0026thinsp;+\u0026thinsp;PD1i vs 9-Ab CT\u0026thinsp;+\u0026thinsp;PD1i\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.5 vs 19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.063 to 17.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNOTE: Data were compared with log-rank (Mantel-Cox) tests.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eTNBC patients are promising candidates for MSP-targeted oligoclonal antibody treatment\u003c/h2\u003e \u003cp\u003eTo inform the feasibility of applying an antibody cocktail-based approach to the treatment of human breast cancer, we explored the breast cancer neoepitope space using mutational data from The Cancer Genome Atlas (TCGA), comparing matched tumor and normal blood samples from TNBC (n\u0026thinsp;=\u0026thinsp;100) and other breast cancer (n\u0026thinsp;=\u0026thinsp;83) patients. Missense mutations within protein-coding genes comprised the majority of detected mutations for both TNBC and other breast cancers (84% and 82%, respectively), with slight variations in overall mutation type distributions between these two groups of patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe numbers of mutated surface neoepitopes for these 183 patients were calculated, revealing 16,758 unique missense mutations. The median numbers of MSPs in patients with TNBC and other forms of breast cancer patients were 13.5 and 8, respectively, with a much broader spread in the distribution of mutated membrane neoepitope counts for TNBC patients relative to those with other types of breast cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea-c). Our preclinical animal data shown previously demonstrated that targeting 9 or 10 MSPs were sufficient to achieve high levels of antibody binding to tumors and effectively inhibit tumor growth (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Guided by these preliminary data and using a cut-off of 10 MSPs per tumor, we found that a significantly higher proportion of TNBC patients harbored sufficient MSPs (\u0026gt;\u0026thinsp;10) to be good candidates to produce a cocktail of MSP-targeting antibodies relative to non-TNBC patients (69% vs. 42%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDespite the lack of conventional therapeutic targets in TNBC and associated treatment difficulties, our results suggest that the neoepitope space for this subtype of breast cancer may be even more expansive than that for other breast cancers. Strikingly, despite the high number of MSPs detected in this cohort of breast cancer patients, we found that the associated missense mutations tended to be patient-specific such that only 2.4% of 3,106 total MSP mutations were shared with two or more TNBC patients, while 97.6% were unique. Similarly, 0.2% of 3,065 MSP mutations were shared among other breast cancer patients, with the remaining 99.8% being unique (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). While they are thus poor candidate targets for the mass production of tumor-engaging antibodies, these neoepitopes highlight an ideal and novel opportunity for the personalized treatment of breast cancer by administering a patient-specific cocktail of antibodies targeting a panel of tumor-associated MSPs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eTNBC tumors account for 10\u0026ndash;15% of breast cancer diagnoses, and their poor responsivity to treatment and tendency towards invasive growth are associated with poor prognostic outcomes for patients with advanced disease (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). While optimal candidate targets suitable for the treatment of all TNBC cases have not been identified, the high mutational burden in these tumors provides a unique opportunity to target patient-specific tumor neoantigens using antibodies or other immunotherapies (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). In this study, we employed an optimized version of our previously reported MSP-targeting antibody cocktail strategy, leading to the successful generation of a cocktail of TNBC cell-binding pAbs with ADCC activity that successfully slowed tumor growth and prolonged survival \u003cem\u003ein vivo.\u003c/em\u003e These promising preclinical efficacy results, coupled with our finding that approximately 69% of TNBC patients are good candidates for MSP-targeting antibody production, support the feasibility of this approach to personalized TNBC patient care.\u003c/p\u003e \u003cp\u003eIn this study, we successfully produced pAbs targeting 12 selected MSPs at a high titer. Despite high peptide affinity in initial ELISAs, 3 of these 12 pAbs showed minimal binding to EMT6 cells. Strikingly, however, the 9 remaining pAbs showed individual binding to cells and were able to bind these target tumor cells in a cumulative manner, confirming the success of our production strategy. This multi-antibody approach to tumor cell targeting may also afford therapeutic advantages. In addition to our demonstrated success in disrupting tumor growth through cocktail-based treatment strategies (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), we have also highlighted the feasibility of utilizing multiple antibodies targeting distinct antigens as an approach to superior single-tumor imaging (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Notably, a study focused on the bispecific antibody (BsAb)-based targeting of HER2-positive tumor cells also demonstrated that the simultaneous application of two lower affinity anti-HER2 BsAbs was associated with improved overall therapeutic efficacy attributable to avidity-driven effects (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Whether the cumulative binding of MSP-targeting antibody cocktails can provide similar avidity-based therapeutic advantages remains to be established given the distinct mechanism of action from CD3-engaging BsAbs, but holds promise as an avenue for further study, particularly given the interplay between antibody avidity, affinity, and the elicitation of ADCC and other effector functions (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). While producing neoantigen-directed therapies is inherently complex and resource-intensive given their patient specificity, other clinical studies to date have highlighted the clinical feasibility of personalized tumor vaccines or adoptive cell transfer-based approaches (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The MSP-targeting antibody cocktail strategy is a novel approach in this therapeutic space, contributing a new tool for the arsenal of antitumor therapies.\u003c/p\u003e \u003cp\u003eTumor growth inhibition and prolonged survival in EMT6 tumor-bearing mice treated with MSP-targeting pAb cocktail mirrors similar successes we have achieved in murine models of melanoma and other tumors (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), providing the first direct evidence that this strategy can be applied to the treatment of TNBC. This antibody-mediated suppression of tumor growth, coupled with the strong binding of these antibodies to the surfaces of tumors but not normal tissues and their \u003cem\u003ein vitro\u003c/em\u003e ADCC activity, is consistent with a model wherein these antibodies can coat the surfaces of MSP-expressing TNBC cells, inducing the killing of these cells by cytotoxic immune effector cell populations. While we did not characterize the precise immune cell populations that underlie this response \u003cem\u003ein vivo\u003c/em\u003e, natural killer (NK) cells are likely to at least partially mediate this effect (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), with potential contributions from other immune cell types. Notably, we administered the antibody cocktail in combination with a PD-1 immune checkpoint inhibitor antibody, as combination treatment strategies, including PD-1/PD-L1 blockade, can more effectively sensitize the tumor microenvironment to a range of treatments (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Combining a cocktail-based treatment strategy with other therapies, such as endocytosis inhibitors reportedly capable of sensitizing tumors to ADCC-mediated tumor cell killing (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), may afford even better therapeutic outcomes, although additional studies will be necessary to test this possibility.\u003c/p\u003e \u003cp\u003eStrikingly, a more substantial proportion of human TNBC patients were classified as promising candidates for this MSP-targeting antibody cocktail-based treatment approach (defined by the presence of 10\u0026thinsp;+\u0026thinsp;MSPs in sequenced tumor samples) as compared to patients with other forms of breast cancer (69% vs. 42%). This observation aligns well with a prior study evaluating the breast cancer neoepitope space in which TNBC was associated with the highest total mutational burden, followed by HER2\u0026thinsp;+\u0026thinsp;breast tumors (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Interestingly, that study noted that just 51% of the predicted neoepitopes were detectably expressed at the RNA level (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), which may account for the lack of observed binding activity for 3 out of 12 pAbs developed here in the EMT6 model system. These results further reinforce the importance of generating an antibody cocktail targeting a sufficient number of MSPs for each patient to maximize the odds of successfully producing multiple therapeutically active antibodies to take advantage of the heterogeneous neoantigen landscape in breast tumors (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Future improvements to the computational approaches used to detect candidate neoepitopes and predict their expression may help refine the selection of suitable candidate MSPs to achieve higher rates of antibody binding (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e), potentially translating to superior therapeutic efficacy given the observed additive binding of different MSP-targeting antibodies to tumor cells in the present study.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn summary, these results highlight the feasibility of developing and administering a cocktail of antibodies targeting TNBC-associated neoepitopes present in individual patients\u0026rsquo; tumors to improve survival through ADCC-mediated target tumor cell killing. Considering the promise of this therapeutic approach, we have applied for and received approval from the US Food and Drug Administration (FDA) to launch a phase I clinical trial enrolling stage IV patients with TNBC and other forms of cancer to test the clinical feasibility and safety of an MSP-targeting antibody cocktail-based therapeutic pipeline (IND 171136). While more work will be essential to deploy this approach more broadly, we anticipate that the findings from this trial will form the evidentiary foundation for further optimization and expansion, providing TNBC patients with individualized therapeutic regimens that can achieve better outcomes not possible under the current standard of care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eADCC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Antibody-dependent cellular cytotoxicity\u003c/p\u003e\n\u003cp\u003eBsAb\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Bispecific antibody\u003c/p\u003e\n\u003cp\u003eCOVID-19\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Coronavirus disease 2019\u003c/p\u003e\n\u003cp\u003eDAPI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;4\u0026apos;,6-diamidino-2-phenylindole\u003c/p\u003e\n\u003cp\u003eDPI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Days post-implantation\u003c/p\u003e\n\u003cp\u003eECD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Extracellular domain\u003c/p\u003e\n\u003cp\u003eELISA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Enzyme-linked immunosorbent assay\u003c/p\u003e\n\u003cp\u003eEMEM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Eagle\u0026apos;s minimum essential medium\u003c/p\u003e\n\u003cp\u003eER\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Estrogen receptor\u003c/p\u003e\n\u003cp\u003eFBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Fetal bovine serum\u003c/p\u003e\n\u003cp\u003eFDA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Food and Drug Administration\u003c/p\u003e\n\u003cp\u003eHER2\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Human epidermal growth factor receptor 2\u003c/p\u003e\n\u003cp\u003eHRP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Horseradish peroxidase\u003c/p\u003e\n\u003cp\u003eIACUC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Institutional Animal Care and Use Committee\u003c/p\u003e\n\u003cp\u003eIgG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Immunoglobulin G\u003c/p\u003e\n\u003cp\u003eKLH\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Keyhole limpet hemocyanin\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLDH\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Lactate dehydrogenase\u003c/p\u003e\n\u003cp\u003eMSP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mutated cell surface proteins\u003c/p\u003e\n\u003cp\u003epAbs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Polyclonal antibodies\u003c/p\u003e\n\u003cp\u003ePBMC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Peripheral blood mononuclear cells\u003c/p\u003e\n\u003cp\u003ePD-1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Programmed cell death protein 1\u003c/p\u003e\n\u003cp\u003ePR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Progesterone receptor\u003c/p\u003e\n\u003cp\u003eTCGA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The Cancer Genome Atlas\u003c/p\u003e\n\u003cp\u003eTMB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;3,3\u0026apos;,5,5\u0026apos;-Tetramethylbenzidine\u003c/p\u003e\n\u003cp\u003eTNBC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Triple-negative breast cancer\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in the study following the University Vermont Institutional Review Board Regulations (Study #00000317). All animal work was completed in accordance with University of Vermont Institutional Animal Care and Use Committee (Protocol #18-002) This study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSCP, GSS, YS, and DNK are shareholders of Moonshot Antibodies, Inc. \u0026nbsp; All other authors have no relevant financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSD Ireland Cancer Research Fund and John Wayne Cancer Foundation supported this work. \u0026nbsp;Imaging was performed at the Microscopy Imaging Center at the University of Vermont (RRID# SCR_018821). \u0026nbsp;Bioinformatics services were provided by the Vermont Integrative Genomics Resource DNA Facility and supported the UVM Larner College of Medicine\u003cstrong\u003e\u0026nbsp;(\u003c/strong\u003eRRID# SCR_021775). The funding bodies had no role in the design of the study and collection, analysis, and interpretation of the data or writing the manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSP contributed to the conceptualization, data curation, data analysis, investigation, methodology, project administration, and writing/review/editing of the manuscript. GS contributed to the conceptualization, data curation, formal analysis, investigation, methodology and preparation/review of manuscript. YS, MA, CH, RB, LM, FZ, and MF contributed to data curation, investigation, methodology and review of the manuscript. DK contributed to the conceptualization, data analysis, investigation, project administration, and writing/review/editing of the manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWilliams MJ, Werner B, Barnes CP, Graham TA, Sottoriva A. Identification of neutral tumor evolution across cancer types. Nat Genet. 2016;48(3):238-44.\u003c/li\u003e\n\u003cli\u003eHand PH, Nuti M, Colcher D, Schlom J. Definition of antigenic heterogeneity and modulation among human mammary carcinoma cell populations using monoclonal antibodies to tumor-associated antigens. Cancer Res. 1983;43(2):728-35.\u003c/li\u003e\n\u003cli\u003eBasanta D, Anderson AR. Exploiting ecological principles to better understand cancer progression and treatment. Interface Focus. 2013;3(4):20130020.\u003c/li\u003e\n\u003cli\u003eMarusyk A, Polyak K. Tumor heterogeneity: causes and consequences. Biochim Biophys Acta. 2010;1805(1):105-17.\u003c/li\u003e\n\u003cli\u003eGreaves M, Maley CC. Clonal evolution in cancer. Nature. 2012;481(7381):306-13.\u003c/li\u003e\n\u003cli\u003eTran TXM, Jung SY, Lee EG, Cho H, Kim NY, Shim S, et al. Fear of Cancer Recurrence and Its Negative Impact on Health-Related Quality of Life in Long-term Breast Cancer Survivors. Cancer Res Treat. 2022;54(4):1065-73.\u003c/li\u003e\n\u003cli\u003eMurthy RK, Loi S, Okines A, Paplomata E, Hamilton E, Hurvitz SA, et al. Tucatinib, Trastuzumab, and Capecitabine for HER2-Positive Metastatic Breast Cancer. N Engl J Med. 2020;382(7):597-609.\u003c/li\u003e\n\u003cli\u003eSledge GW, Jr., Toi M, Neven P, Sohn J, Inoue K, Pivot X, et al. The Effect of Abemaciclib Plus Fulvestrant on Overall Survival in Hormone Receptor-Positive, ERBB2-Negative Breast Cancer That Progressed on Endocrine Therapy-MONARCH 2: A Randomized Clinical Trial. JAMA Oncol. 2020;6(1):116-24.\u003c/li\u003e\n\u003cli\u003eHurvitz SA, Hegg R, Chung WP, Im SA, Jacot W, Ganju V, et al. Trastuzumab deruxtecan versus trastuzumab emtansine in patients with HER2-positive metastatic breast cancer: updated results from DESTINY-Breast03, a randomised, open-label, phase 3 trial. Lancet. 2023;401(10371):105-17.\u003c/li\u003e\n\u003cli\u003eSchmid P, Cortes J, Pusztai L, McArthur H, K\u0026uuml;mmel S, Bergh J, et al. Pembrolizumab for Early Triple-Negative Breast Cancer. N Engl J Med. 2020;382(9):810-21.\u003c/li\u003e\n\u003cli\u003eBraster R, O\u0026apos;Toole T, van Egmond M. Myeloid cells as effector cells for monoclonal antibody therapy of cancer. Methods. 2014;65(1):28-37.\u003c/li\u003e\n\u003cli\u003eParrillo JE, Fauci AS. Apparent direct cellular cytotoxicity mediated via cytophilic antibody. Multiple Fc receptor bearing effector cell populations mediating cytophilic antibody induced cytotoxicity. Immunology. 1977;33(6):839-50.\u003c/li\u003e\n\u003cli\u003eParakh S, Gan HK, Parslow AC, Burvenich IJ, Burgess AW, Scott AM. Evolution of anti-HER2 therapies for cancer treatment. Cancer treatment reviews. 2017;59:1-21.\u003c/li\u003e\n\u003cli\u003eNarang P, Chen M, Sharma AA, Anderson KS, Wilson MA. The neoepitope landscape of breast cancer: implications for immunotherapy. Bmc Cancer. 2019;19:1-10.\u003c/li\u003e\n\u003cli\u003eBrennick CA, George MM, Corwin WL, Srivastava PK, Ebrahimi-Nik H. Neoepitopes as cancer immunotherapy targets: key challenges and opportunities. Immunotherapy. 2017;9(4):361-71.\u003c/li\u003e\n\u003cli\u003eJoubert S, Stuible M, Lord-Dufour S, Lamoureux L, Vaillancourt F, Perret S, et al. A CHO stable pool production platform for rapid clinical development of trimeric SARS-CoV-2 spike subunit vaccine antigens. Biotechnol Bioeng. 2023;120(7):1746-61.\u003c/li\u003e\n\u003cli\u003ePero SC, Nagulapally AB, Mei L, Zhang F, Sholler GS, Krag DN, Shukla GS. Development of Clinical-Grade Antibodies against Tumor-Specific Mutations to Target Neuroblastoma. Ann Clin Lab Sci. 2022;52(3):349-58.\u003c/li\u003e\n\u003cli\u003eShukla G, Pero S, Sun Y-J, Mei L, Zhang F, Sholler G, Krag D. Multiple antibodies targeting tumor-specific mutations redirect immune cells to inhibit tumor growth and increase survival in experimental animal models. Clinical and Translational Oncology. 2020;22:1094-104.\u003c/li\u003e\n\u003cli\u003eSoudy M, Anwar AM, Ahmed EA, Osama A, Ezzeldin S, Mahgoub S, Magdeldin S. UniprotR: Retrieving and visualizing protein sequence and functional information from Universal Protein Resource (UniProt knowledgebase). Journal of Proteomics. 2020;213:103613.\u003c/li\u003e\n\u003cli\u003eUniProt: the Universal Protein Knowledgebase in 2023. Nucleic Acids Res. 2023;51(D1):D523-d31.\u003c/li\u003e\n\u003cli\u003eTeam RC. R: A language and environment for statistical computing. Foundation for Statistical Computing, Vienna, Austria. 2013.\u003c/li\u003e\n\u003cli\u003eAllaire J. RStudio: integrated development environment for R. Boston, MA. 2012;770(394):165-71.\u003c/li\u003e\n\u003cli\u003eRockwell SC, Kallman RF, Fajardo LF. Characteristics of a serially transplanted mouse mammary tumor and its tissue-culture-adapted derivative. Journal of the National Cancer Institute. 1972;49(3):735-49.\u003c/li\u003e\n\u003cli\u003eXiao Y, Zheng P, Xu W, Wu Z, Zhang X, Wang R, et al. Progesterone receptor impairs immune respond and down-regulates sensitivity to anti-LAG3 in breast cancer. Transl Res. 2024;271:68-78.\u003c/li\u003e\n\u003cli\u003eShukla GS, Sun Y-J, Pero SC, Krag DN. A cocktail of polyclonal affinity enriched antibodies against melanoma mutations increases binding and inhibits tumor growth. Journal of immunological methods. 2020;478:112720.\u003c/li\u003e\n\u003cli\u003eZagami P, Carey LA. Triple negative breast cancer: Pitfalls and progress. NPJ breast cancer. 2022;8(1):95.\u003c/li\u003e\n\u003cli\u003eBenvenuto M, Focaccetti C, Izzi V, Masuelli L, Modesti A, Bei R, editors. Tumor antigens heterogeneity and immune response-targeting neoantigens in breast cancer. Seminars in Cancer Biology; 2021: Elsevier.\u003c/li\u003e\n\u003cli\u003eSun Y, Shukla G, Pero SC, Currier E, Sholler G, Krag D. Single tumor imaging with multiple antibodies targeting different antigens. Biotechniques. 2012;52(4).\u003c/li\u003e\n\u003cli\u003eSlaga D, Ellerman D, Lombana TN, Vij R, Li J, Hristopoulos M, et al. Avidity-based binding to HER2 results in selective killing of HER2-overexpressing cells by anti-HER2/CD3. Science translational medicine. 2018;10(463):eaat5775.\u003c/li\u003e\n\u003cli\u003eOostindie SC, Lazar GA, Schuurman J, Parren PW. Avidity in antibody effector functions and biotherapeutic drug design. Nature Reviews Drug Discovery. 2022;21(10):715-35.\u003c/li\u003e\n\u003cli\u003eLybaert L, Thielemans K, Feldman SA, van der Burg SH, Bogaert C, Ott PA. Neoantigen-directed therapeutics in the clinic: where are we? Trends in cancer. 2023;9(6):503-19.\u003c/li\u003e\n\u003cli\u003eDixon KJ, Wu J, Walcheck B. Engineering anti-tumor monoclonal antibodies and Fc receptors to enhance ADCC by human NK cells. Cancers. 2021;13(2):312.\u003c/li\u003e\n\u003cli\u003eYi M, Zheng X, Niu M, Zhu S, Ge H, Wu K. Combination strategies with PD-1/PD-L1 blockade: current advances and future directions. Molecular cancer. 2022;21(1):28.\u003c/li\u003e\n\u003cli\u003eChew HY, De Lima PO, Cruz JLG, Banushi B, Echejoh G, Hu L, et al. Endocytosis inhibition in humans to improve responses to ADCC-mediating antibodies. Cell. 2020;180(5):895-914. e27.\u003c/li\u003e\n\u003cli\u003eRocha LGdN, Guimar\u0026atilde;es PAS, Carvalho MGR, Ruiz JC. Tumor Neoepitope-Based Vaccines: A Scoping Review on Current Predictive Computational Strategies. Vaccines. 2024;12(8):836.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Triple-negative breast cancer, mutated cell surface protein-targeting antibodies, somatic missense mutation, antibody-dependent cellular cytotoxicity, tumor growth inhibition","lastPublishedDoi":"10.21203/rs.3.rs-6073571/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6073571/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTreatment options for triple-negative breast cancer (TNBC) remain limited, and the highly heterogeneous nature of these tumors often contributes to therapeutic resistance. While we have previously demonstrated that preparing a cocktail of antibodies targeting multiple distinct mutated cell surface proteins (MSPs) harboring neoepitopes unique to a given tumor can effectively disrupt tumor growth in mice, the feasibility of this approach in treating TNBC has yet to be tested.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e We used the murine EMT6 cell line to model TNBC, comparing the EMT6 cell genome to that of parental BALB/c mice to guide the production of polyclonal antibodies (pAbs) targeting 12 different EMT6-specific MSPs. Antibody binding to purified peptides, EMT6 cells, and healthy tissues was assessed through immunofluorescence staining. EMT6 tumor-bearing mice were established and treated with a pAb cocktail in combination with anti-PD-1, and tumor growth and survival were monitored. A bioinformatics-based survey of genomic data from TNBC patients in The Cancer Genome Atlas (TCGA) database was conducted to assess MSP prevalence.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 12 pAb preparations, 9 successfully bound to EMT6 cell surfaces in a cumulative manner without detectable non-tumor binding. When we administered a cocktail of these 9 MSP-targeting pAbs to EMT6 tumor-bearing mice, delayed tumor growth and improved survival were observed. Analyses of the TCGA cohort of TNBC patients revealed that the tumors of a larger proportion of these patients harbored\u0026thinsp;\u0026gt;\u0026thinsp;10 MSPs as compared to individuals with other forms of breast cancer (69% vs. 42%), making them particularly good candidates for MSP-specific antibody cocktail treatment.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eTogether, these results highlight the promise of using antibodies directed against MSPs expressed by TNBC tumor cells to kill tumor cells \u003cem\u003ein vivo\u003c/em\u003e, providing a unique approach to individualized cancer patient care with the potential to achieve superior patient outcomes through the elimination of heterogeneous tumor cell populations.\u003c/p\u003e","manuscriptTitle":"Novel antibody cocktail therapy targeting extracellular tumor-specific mutations to treat triple-negative breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-10 09:54:39","doi":"10.21203/rs.3.rs-6073571/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"91ef3052-1723-44d2-83a4-a03374aa6e9a","owner":[],"postedDate":"March 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-30T19:27:39+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-10 09:54:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6073571","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6073571","identity":"rs-6073571","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}