Antibody Clone Research Articles

Development of Optimized Strategy for Cloning, Expression and Analysis of a Recombinant Anti-CD20 Therapeutic Monoclonal Antibody in HEK-293 Cells

The significance of expression systems for quickly creating enough numbers of therapeutic monoclonal antibodies to make them available to patients has been heightened in recent years due to advances in the creation of genetically modified monoclonal antibodies. The conventional method for making recombinant proteins involves first cloning the desired gene into an expression vector, and then testing how well it expresses itself in cells. For cellular expression and perpetuation, a plasmid containing the chosen genes is then cloned. The most significant and lucrative subset of biopharmaceuticals is monoclonal antibodies (mAbs). To temporarily produce an anti-CD20 monoclonal antibody in mammalian cells, this work created and assessed an antiCD20 mAb expression construct. The gene fragment was transferred to the expression vector after the vector (pcDNA3.1+) was synthesised by sequentially cloning the Light Chain (LC) and Heavy Chain (HC). We co-transfected HEK 293 cells and then examined the cell culture supernatant for antibody clone expression. Using this technology to transiently express the whole monoclonal antibody in mammalian cells was a breeze, and our findings prove it.

Evaluation of the level expression of the Russian clone of PD-L1 antibodies and comparison with validated clones from other manufacturers on stomach cancer material

The study of immunotherapeutic markers is one of the most popular and promising areas in oncology. One of the most studied targets of immunotherapy is the ligand of the programmed cell death protein 1 (PD-L1). All diagnostic kits for determining PD-L1 expression in tumors are of foreign origin. To ensure the technological sovereignty of the Russian Federation in the field of medical technologies, it is necessary to conduct research with a domestic clone of PD-L1 antibodies and compare the results with already validated analogues. The aim of the work was to evaluate the expression of a domestic clone of antibodies to PD-L1 (PBM-1A4), determine its relationship with the clinical and morphological parameters of gastric cancer and compare the expression of various PD-L1 clones in gastric cancer (SP142, SP263, 22C3 and PBM-1A4). The study was performed on samples of gastric cancer surgical material from 131 patients who had not received chemotherapy, radiation or immunotherapy before surgery. Results: PD-L1 expression detected by the PBM-1A4 antibody clone is present in 46.2% of gastric cancer samples. Among PD-L1(PBM-1A4)-positive tumors, neoplasms of the second macroscopic type according to R. Bormann and tubular adenocarcinomas significantly predominate. The SP142 clone shows the greatest consistency with PBM 1A4 expression (significant consistency, Cohen's kappa is 0.67335). Conclusion: This antibody clone undoubtedly represents an extremely promising development by Russian scientists, which makes it possible to make the molecular diagnosis of malignant neoplasms more accessible to Russian patients.

Folate Receptor Alpha Expression and the Tumor Immune Microenvironment in Patients with Cervical Cancer.

Folate receptor α (FRα) is a cell-surface protein and an attractive target for cancer treatment. We investigated the association between FRα expression and the tumor immune microenvironment in patients with cervical cancer. We examined whole tumor sections of 123 patients with cervical cancer: 67 and 56 sections of squamous cell carcinoma (SCC) and non-SCC, respectively. FRα expression was assessed using immunohistochemical staining with the anti-FRα monoclonal antibody clone 26B3. Programmed death-ligand 1 (PD-L1) expression was assessed using a combined positive score (CPS). The intratumoral CD3 and CD8 cell densities were calculated as the average number of positive cells in five independent areas. FRα-positivity was identified in 72.4% of the patients, and it differed by histology (SCC vs. non-SCC; 55.2% vs. 92.9%, P<0.001). PD-L1 status was positive (CPS ≥1) in 75.6% and was more commonly expressed in patients with SCC (SCC vs. non-SCC; 83.5% vs. 66.1%, P=0.02). FRα expression had a weak correlation with PD-L1 expression (r=-0.22, P<0.001) and CD8-positive cells (r=-0.19, P=0.03). FRα-positivity was more frequently observed in the PD-L1 CPS <10 group than in the PD-L1 CPS ≥10 group (81% vs. 64%, P=0.03). FRα-high was significantly associated with poor prognosis, especially in the PD-L1 CPS ≥10 groups (hazard ratio: 4.10, 95% confidence interval: 1.39-12.06, P=0.01). In conclusion, FRα expression was higher in patients with cervical cancer and PD-L1 CPS <10 than in those with CPS ≥10. Targeting FRα expression may be a potential therapeutic strategy for cervical cancer patients with low or negative PD-L1 expression.

The presence of broadly neutralizing anti-SARS-CoV-2 RBD antibodies elicited by primary series and booster dose of COVID-19 vaccine.

Antibody-mediated immunity plays a key role in protection against SARS-CoV-2. We characterized B-cell-derived anti-SARS-CoV-2 RBD antibody repertoires from vaccinated and infected individuals and elucidate the mechanism of action of broadly neutralizing antibodies and dissect antibodies at the epitope level. The breadth and clonality of anti-RBD B cell response varies among individuals. The majority of neutralizing antibody clones lose or exhibit reduced activities against Beta, Delta, and Omicron variants. Nevertheless, a portion of anti-RBD antibody clones that develops after a primary series or booster dose of COVID-19 vaccination exhibit broad neutralization against emerging Omicron BA.2, BA.4, BA.5, BQ.1.1, XBB.1.5 and XBB.1.16 variants. These broadly neutralizing antibodies share genetic features including a conserved usage of the IGHV3-53 and 3-9 genes and recognize three clustered epitopes of the RBD, including epitopes that partially overlap the classically defined set identified early in the pandemic. The Fab-RBD crystal and Fab-Spike complex structures corroborate the epitope grouping of antibodies and reveal the detailed binding mode of broadly neutralizing antibodies. Structure-guided mutagenesis improves binding and neutralization potency of antibody with Omicron variants via a single amino-substitution. Together, these results provide an immunological basis for partial protection against severe COVID-19 by the ancestral strain-based vaccine and indicate guidance for next generation monoclonal antibody development and vaccine design.

The peculiar features, diversity and impact of citrulline-reactive autoantibodies.

Since entering the stage 25 years ago as a highly specific serological biomarker for rheumatoid arthritis, anti-citrullinatedprotein antibodies (ACPAs) have been a topic of extensive research. This hallmark B cell response arises years before disease onset, displays interpatient autoantigen variability, and is associated with poor clinical outcomes. Technological and scientific advances have revealed broad clonal diversity and intriguing features including high levels of somatic hypermutation, variable-domain N-linked glycosylation, hapten-like peptide interactions, and clone-specific multireactivity to citrullinated, carbamylated and acetylated epitopes. ACPAs have been found in different isotypes and subclasses, in both circulation and tissue, and are secreted by both plasmablasts and long-lived plasma cells. Notably, although some disease-promoting features have been reported, results now demonstrate that certain monoclonal ACPAs therapeutically block arthritis and inflammation in mouse models. A wealth of functional studies using patient-derived polyclonal and monoclonal antibodies have provided evidence for pathogenic and protective effects of ACPAs in the context of arthritis. To understand the roles of ACPAs, one needs to consider their immunological properties by incorporating different facets such as rheumatoid arthritis B cell biology, environmental triggers and chronic antigen exposure. The emerging picture points to a complex role of citrulline-reactive autoantibodies, in which the diversity and dynamics of antibody clones could determine clinical progression and manifestations.

Elucidating key determinants of engineered scFv antibody in MMP-9 binding using high throughput screening and machine learning.

An imbalance in matrix metalloproteinase-9 (MMP-9) regulation can lead to numerous diseases, including neurological disorders, cancer, and pre-term labor. Engineering single-chain antibody fragments (scFvs) Targeting MMP-9 to develop novel therapeutics for such diseases is desirable. We screened a synthetic scFv antibody library displayed on the yeast surface for binding improvement to MMP-9 using FACS (fluorescent-activated cell sorting). The scFv antibody clones isolated after FACS showed improvement in binding to MMP-9 compared to the endogenous inhibitor. To understand molecular determinants of binding between engineered scFv antibody variants and MMP-9, next-generation DNA sequencing, and computational protein structure analysis were used. Additionally, a deep-learning language model was trained on the synthetic library to predict the binding of scFv variants using their CDR-H3 sequences.

Digital versus manual pathology scoring of PD-L1 in patients with esophageal squamous cell carcinoma (ESCC).

e16023 Background: Immune checkpoint inhibitors (ICIs) are standard-of-care for patients with ESCC, but the association between PD-L1 and clinical outcomes of patients with ESCC receiving ICIs treatment is unclear. Currently, different PD-L1 antibody clones, scoring, and cutoffs were used for different ICIs development in ESCC. Thus, we develop a digital pathology (DP) algorithm to generate multiple scores at the same time with high reproducibility. We evaluate DP algorithm by: (1) comparing the digital and manual scores of SP263 and 22C3 assays; (2) evaluating the association with OS. Methods: Tumor tissue samples were collected from ESCC patients treated at National Taiwan University Hospital between 2017 and 2020. Slides were tested for PD-L1 using SP263 and 22C3 assays at a College of American Pathologists accredited central laboratory. H&amp;E and PD-L1 slides were scanned for whole slide images (WSIs) using DP200 scanner at 20x. HALO (v3.5) by indica labs was used for DP development by deep learning neural network algorithms. WSIs of SP263 were annotated for region of interest (ROI), tumor/stroma area, and tumor, immune and fibroblast cells by board certified pathologists. After the algorithm is developed and run on SP263 WSIs, a board-certified pathologist reviewed the images and provided an agreement score of DP markups. The images were excluded if an agreement was less than 80%. This algorithm was then applied to 22C3 WSIs. Data of areas and cells were exported for subsequent statistical analysis using R. We calculated the DP scores based on the definition of manual readouts of TAP, CPS and s/iTILs in ROI and tumor and stroma regions in both clones’ WSIs. These DP scores were compared with manual scores using Spearman’s rank-order correlation. Association with OS were evaluated using cox proportional hazard regression. Results: Of 235 evaluable images, twelve (5.1%) were excluded due to the low agreement with the pathologist's judgment. DP generated scores showed a strong correlation with pathologists scoring (rho = 0.80 for SP263 and rho = 0.74 for 22C3). DP generated CPS-like and TAP-like scores in ROI, and tumor and stroma regions from SP263 and 22C3 also demonstrated a strong correlation between each other (rho: 0.77 - 0.86). However, s/iTILs correlation between DP and pathologist score is negligible (rho: 0.002 - 0.34). While examining the association of PD-L1 scores and s/iTILs with OS, no clear associations were found with either DP or pathologists’ scores, after adjusting for stage, ECOG, age and gender. Conclusions: DP algorithms developed in this study demonstrated the efficiency of generating multiple DP scores of CPS, TAP, and s/iTILs from one image at the same time, which performed comparable to manual scores. DP algorithm developed based on SP263 is generalizable to 22C3 and showed a good performance. Further algorithm adjustment will be made to overcome the misclassification in the 12 failed cases.

Follow-up on phase 1 study of AT101, a novel anti-CD19 chimeric antigen receptor cell therapy (CAR-T) in patients with relapsed or refractory (r/r) b-cell non-Hodgkin lymphoma.

7035 Background: All the FDA-approved CD19 CAR-T products are based on FMC63 scFv, which binds to the membrane-distal region of CD19. We developed a novel anti-CD19 antibody clone (1218) binding to a membrane-proximal epitope of CD19 with fast on/off kinetics. AT101 is an autologous CAR-T cell transduced with a lentiviral vector encoding CAR comprised of a humanized scFv of 1218, 4-1BB costimulatory, and CD3zeta domain. Methods: In the phase 1 trial, patients (n=3 per dose level; up to n=18 in total) are treated with AT101 in 3 dose-escalation cohorts based on a standard 3 + 3 design. Each patient received a single intravenous dose of AT101 at dose level (DL) 1 (0.2 x 106 cells/kg), DL2 (1.0 x 106 cells/kg), or DL3 (5.0 x 106 cells/kg). The primary objective is to determine the safety, the maximum tolerated dose, and the recommended phase 2 dose of AT101. Key eligibility criteria include patients aged ≥19 with histologically confirmed relapsed or refractory B-cell non-Hodgkin lymphoma (NHL). Tumor responses were evaluated using Lugano 2014 criteria at 4 weeks before AT101 infusion as well as at 4 weeks and 3, 6, 9, 12, and 18 months after AT101 infusion. Results: From March 2022 to December 2022, fourteen patients were enrolled and 12 patients were treated, who were their median age of 62.5 years (range 39 to 84) and received a median of three prior lines of therapy (range 2-9). Their subtypes were as follows: diffuse large B cell lymphoma (DLBCL; n=7, 58.3%), follicular lymphoma (FL; n=3, 25.0%), mantle cell lymphoma (MCL; n=1, 8.3%), or marginal zone lymphoma (MZL; n=1, 8.3%)). The data collection cut-off date was January 31, 2024. Based on the best overall response up to three months, eleven patients responded with an overall response rate (ORR) of 91.7%, and a complete response (CR) was observed in nine patients (75%). Remarkably, in DL2 and DL3 groups, the CR was 100.0%. Among nine patients who achieved CR, seven patients have remained in CR during the median follow-up of 13.6 months (1.6-22.3 months). One patient experienced relapse and another one died from septic shock. The median duration of response (DOR), progression-free survival (PFS), overall survival (OS), and event-free survival (EFS) were 19.5, 17.2, 18.9 and 17.2 months, respectively. The median DOR, PFS, OS and EFS were not reached. Conclusions: In this first-in-human phase 1 trial, AT101 was tolerable with limited and manageable toxicities. In comparison to current FMC63 scFv-based CD19 CAR-T therapies, AT101 exhibited potent and more enduring efficacy with a remarkable suppression of relapse after CR. A phase 2 clinical trial is currently under-going for DLBCL patients. Clinical trial information: NCT05338931 .

PET imaging of Aspergillus infection using Zirconium-89 labeled anti-β-glucan antibody fragments

PurposeInvasive fungal diseases, such as pulmonary aspergillosis, are common life-threatening infections in immunocompromised patients and effective treatment is often hampered by delays in timely and specific diagnosis. Fungal-specific molecular imaging ligands can provide non-invasive readouts of deep-seated fungal pathologies. In this study, the utility of antibodies and antibody fragments (Fab) targeting β-glucans in the fungal cell wall to detect Aspergillus infections was evaluated both in vitro and in preclinical mouse models.MethodsThe binding characteristics of two commercially available β-glucan antibody clones and their respective antigen-binding Fabs were tested using biolayer interferometry (BLI) assays and immunofluorescence staining. In vivo binding of the Zirconium-89 labeled antibodies/Fabs to fungal pathogens was then evaluated using PET/CT imaging in mouse models of fungal infection, bacterial infection and sterile inflammation.ResultsOne of the evaluated antibodies (HA-βG-Ab) and its Fab (HA-βG-Fab) bound to β-glucans with high affinity (KD = 0.056 & 21.5 nM respectively). Binding to the fungal cell wall was validated by immunofluorescence staining and in vitro binding assays. ImmunoPET imaging with intact antibodies however showed slow clearance and high background signal as well as nonspecific accumulation in sites of infection/inflammation. Conversely, specific binding of [89Zr]Zr-DFO-HA-βG-Fab to sites of fungal infection was observed when compared to the isotype control Fab and was significantly higher in fungal infection than in bacterial infection or sterile inflammation.Conclusions[89Zr]Zr-DFO-HA-βG-Fab can be used to detect fungal infections in vivo. Targeting distinct components of the fungal cell wall is a viable approach to developing fungal-specific PET tracers.

Identification of high-performing antibodies for the reliable detection of Tau proteoforms by Western blotting and immunohistochemistry

Antibodies are essential research tools whose performance directly impacts research conclusions and reproducibility. Owing to its central role in Alzheimer’s disease and other dementias, hundreds of distinct antibody clones have been developed against the microtubule-associated protein Tau and its multiple proteoforms. Despite this breadth of offer, limited understanding of their performance and poor antibody selectivity have hindered research progress. Here, we validate a large panel of Tau antibodies by Western blot (79 reagents) and immunohistochemistry (35 reagents). We address the reagents’ ability to detect the target proteoform, selectivity, the impact of protein phosphorylation on antibody binding and performance in human brain samples. While most antibodies detected Tau at high levels, many failed to detect it at lower, endogenous levels. By WB, non-selective binding to other proteins affected over half of the antibodies tested, with several cross-reacting with the related MAP2 protein, whereas the “oligomeric Tau” T22 antibody reacted with monomeric Tau by WB, thus calling into question its specificity to Tau oligomers. Despite the presumption that “total” Tau antibodies are agnostic to post-translational modifications, we found that phosphorylation partially inhibits binding for many such antibodies, including the popular Tau-5 clone. We further combine high-sensitivity reagents, mass-spectrometry proteomics and cDNA sequencing to demonstrate that presumptive Tau “knockout” human cells continue to express residual protein arising through exon skipping, providing evidence of previously unappreciated gene plasticity. Finally, probing of human brain samples with a large panel of antibodies revealed the presence of C-term-truncated versions of all main Tau brain isoforms in both control and tauopathy donors. Ultimately, we identify a validated panel of Tau antibodies that can be employed in Western blotting and/or immunohistochemistry to reliably detect even low levels of Tau expression with high selectivity. This work represents an extensive resource that will enable the re-interpretation of published data, improve reproducibility in Tau research, and overall accelerate scientific progress.

Clinical and humoral response after SARS-CoV-2 breakthrough infection in patients receiving immunosuppressant therapy

BackgroundDespite impaired humoral responses in patients treated with immunosuppressants (ISPs), recent studies found similar severity of SARS-CoV-2 breakthrough infections compared to controls. One potential explanation is the rapid generation humoral responses upon infection, but evidence is lacking. ObjectivesTo investigate longitudinal dynamics of the SARS-CoV-2 antibody repertoire after SARS-CoV-2 delta and omicron breakthrough infections in patients with immune-mediated inflammatory diseases (IMID) on ISPs and controls. MethodsAs prospective sub-study of the national Target-to-B! (T2B!) consortium, we included IMID patients on ISPs and controls who reported SARS-CoV-2 breakthrough infections between July 1, 2021, and April 1, 2022. To get an impression of the dynamics of the antibody repertoire, three antibody titers of wild-type RBD, wild-type S, and omicron RBD were measured at four time points after SARS-CoV-2 breakthrough infections. ResultsWe included 302 IMID patients on ISPs and 178 controls. Antibody titers increased up to 28 days after breakthrough infections in both groups. However, in IMID patients on anti-CD20 therapy and sphingosine-1 phosphate receptor (S1P) modulators, antibody titers were considerably lower compared to controls. In the anti-TNF group, we observed slightly lower antibody titers in the early stages and a faster decline of antibodies after infection compared to controls. Breakthrough infections were mostly mild and hospitalization was required in less than 1% of the cases. ConclusionsMost ISPs do not influence the dynamics of the SARS-CoV-2 antibody repertoire and exhibit a rapid recall response with cross-reactive antibody clones towards new viral variants. However, in patients treated with anti-CD20 therapy or S1P modulators, the dynamics were greatly impaired, and to a lesser extent in those anti-TNF. Nevertheless, only a few severe breakthrough cases were reported.

The role of the size of affinity ligands in the detection and characterization of extracellular vesicles

Surface proteins on the membrane of nano-sized extracellular vesicles (EVs) not only play crucial roles in cell-to-cell communication, but also are specific binding targets for EV detection, isolation and tracking. The low abundance of protein biomarkers on EV surface, the formation of clusters and the complex EV surface network impose significant challenges to the study of EVs. Employing bulky sized affinity ligands, such as antibodies, in the detection and characterization of these vesicles often result in reduced sensitivity of detection or poor quantification of proteins on the EV surface. By virtue of their small size and high specificity, Affibody molecules emerge as a potential alternative to their monoclonal antibody counterparts as robust affinity ligands in EV research. In this study, we present a theoretical framework on the superiority of anti-HER2 Affibodies over anti-HER2 antibodies in labeling and detecting HER2-positive EVs, followed by the demonstration of the advantages of HER2 Affibodies in accessing EV surface and the detection of EVs through multiple types of approaches including fluorescence intensity, colorimetry, and fluorescence polarization. HER2 Affibodies outperformed by 10-fold over three HER2 antibody clones in accessing HER2-positive EVs derived from different human cancer cell lines. Furthermore, HRP-Affibody molecules could detect EVs from cancer cells spiked into human serum with at least a 2-fold higher sensitivity compared with that of their antibody counterparts. In addition, in fluorescence polarization assays in which no separation of free from bound ligand is required, FITC-labeled HER2 Affibodies could sensitively detect HER2-positive EVs with a clinically relevant limit of detection, whilst HER2 antibodies failed to detect EVs in the same conditions. With the demonstrated superiority in accessing and detecting surface targets over bulky-sized antibodies in EVs, Affibodies may become the next-generation of affinity ligands in the precise characterization and quantification of molecular architecture on the surface of EVs.

Performance Analysis of Leica Biosystems Monoclonal Antibody Programmed Cell Death Ligand 1 Clone 73-10 on Breast, Colorectal, and Hepatocellular Carcinomas.

Programmed cell death receptor 1/Programmed cell death ligand 1 (PD-L1) checkpoint pathway is responsible for the control of immune cell responses. Immunotherapy using checkpoint inhibitors, such as anti-PD-L1 therapy, aids disease management and potentiates clinical outcomes. This study aimed to analyze the performance of the Leica Biosystems (LBS) USA FDA class I in vitro diagnostic monoclonal antibody (clone 73-10) to detect PD-L1 expression in breast, colorectal, and hepatocellular carcinomas compared with the class III FDA-approved PD-L1 detecting antibodies [SP263 (Ventana), 22C3 (Dako), and 28-8 (Dako)] using 208 unique tissue microarray-based cases for each tumor type. The interassay concordances between LBS 73-10 clone and other PD-L1 antibodies ranged from 0.59 to 0.95 Cohen kappa coefficient (K) and from 0.66 to 0.90 (K) for cutoff values of 1% and 50% tumor proportion score (TPS), respectively. The 73-10 clones showed inter-pathologist agreements ranging from 0.53 to 1.0 (K) and 0.34 to 0.94 (K) for cutoff values of 1% and 50% TPS, respectively. For the immune cell proportion score (IPS) using a cutoff of 1%, the Kappa coefficient of interassay concordances and inter-pathologist agreements ranged from 0.34 to 0.94. The 73-10 clone assay's sensitivity ranged from 78.3% to 100% (TPS ≥1%), 100% (TPS ≥50%), and 77.4% to 93.5% (IPS ≥1%), while its specificity was 97.9% to 100% (TPS ≥1%), 99.5% to 99.8% (TPS ≥50%), and 97.9% to 100% (IPS ≥1%). This exploratory evaluation of LBS 73-10 monoclonal antibody on a large set of breast, colorectal, and hepatocellular carcinomas showed the assay's technical performance is comparable to the FDA-approved companion/complementary diagnostics PD-L1 detection assays.

Development of a new affinity maturation protocol for the construction of an internalizing anti-nucleolin antibody library

Over the last decades, monoclonal antibodies have substantially improved the treatment of several conditions. The continuous search for novel therapeutic targets and improvements in antibody’s structure, demands for a constant optimization of their development. In this regard, modulation of an antibody’s affinity to its target has been largely explored and culminated in the discovery and optimization of a variety of molecules. It involves the creation of antibody libraries and selection against the target of interest. In this work, we aimed at developing a novel protocol to be used for the affinity maturation of an antibody previously developed by our group. An antibody library was constructed using an in vivo random mutagenesis approach that, to our knowledge, has not been used before for antibody development. Then, a cell-based phage display selection protocol was designed to allow the fast and simple screening of antibody clones capable of being internalized by target cells. Next generation sequencing coupled with computer analysis provided an extensive characterization of the created library and post-selection pool, that can be used as a guide for future antibody development. With a single selection step, an enrichment in the mutated antibody library, given by a decrease in almost 50% in sequence diversity, was achieved, and structural information useful in the study of the antibody-target interaction in the future was obtained.

Abstract PO4-01-08: Co-expression of estrogen receptor (ER), progesterone receptor (PR), and Ki67 in a single breast cancer cell indicates a favorable prognosis in ER-positive breast cancer

Abstract Background: ER-positive breast cancer is biologically and clinically divided into two subtypes: luminal-A and luminal-B. This classification is mainly based on the status of cellular proliferation. At least two different pathways drive cellular proliferation in ER-positive breast cancer. One is a classical pathway where ER binds to estrogen responsive element (ERE), which leads to the expression of downstream molecules, including PR. The other is a non-classical pathway where a complex of ER and relevant factors bind to different sites than ERE. Growth factor signaling has been suggested to potentiate a non-classical pathway. We hypothesized that examining PR status in ER-positive proliferating cells could tell which pathway is more dominant in ER-positive breast cancer. Methods: To test the hypothesis, we used a newly developed triplex immunohistochemistry (IHC) that detects three molecules simultaneously under bright-field microscopy. Postmenopausal patients who were treated with neoadjuvant endocrine therapy with aromatase inhibitors from January 2007 to September 2016 at Saitama Cancer Center were included in this study. ER, PR, and Ki67 expressions were assessed in a single slide using the triplex IHC assay with anti-ER antibody (clone SP1), anti-PR antibody (clone 1E2), and anti-Ki67 antibody (clone 30-9). ER, PR and Ki67 expression was assessed in a single cell nucleus of cancer cells (567 to 4871 cells) from multiple areas in each case. An ER-positive proliferating cell was defined as an ER-positive and Ki67-positive cell. PR status in ER-positive proliferating cells was assessed. When PR was expressed in more than 50% of ER-positive proliferating cells in a clinical case, the tumor was categorized as the PR-positive group. Luminal A and luminal B breast cancers were defined based on the pre-treatment Ki67 labeling index with a cut-off of 14 %. Statistical analyses included the Mann-Whitney test, the log-rank test, and the Cox proportional hazard model. Results: Pre-treatment tissues from 55 patients were evaluated. The median age was 62 (range: 54 to 80) years. The patients were grouped into PR-positive and PR-negative groups. The two groups had no differences in age and pre-treatment T and N stages. The median pre-treatment Ki67 labeling index was 5.9 % in the PR-positive group and 9.9 % in the PR-negative group, which showed a statistically significant difference (P = 0.01). Clinical response to neoadjuvant endocrine therapy was compared, and no difference was observed. The median post-treatment Ki67 labeling index was 3.6 % in the PR-positive group and 13.1 % in the PR-negative group with a significant difference (P = 0.035). The survival was compared between the two groups. The PR-positive group showed a significantly more favorable disease-free survival (DFS) than the PR-negative group (P = 0.0079). To adjust for the background differences including Ki67 and PR status, a multivariate analysis was performed and showed that the PR-positive group had a significantly better DFS than the PR-negative group independent of clinical stage, Ki67 labeling index, and PR status (P = 0.042). Breast cancer-specific survival (BCSS) was also better in the PR-positive group than in the PR-negative group after adjusting for clinical stage, Ki67 labeling index, and PR status (P = 0.043). Interestingly, among patients with luminal A tumors, those in the PR-positive group showed a better DFS than those in the PR-negative group (P = 0.022). Conclusion: PR status in ER-positive proliferating cells was an independent prognostic factor in DFS and BCSS and divided patients with luminal A tumors further into two prognostic groups. Citation Format: Takayuki Ueno, Rie Horii, Hiroshi Matsumoto, Makiko Ono, Yurina Maeshima, Hiroaki Nitta. Co-expression of estrogen receptor (ER), progesterone receptor (PR), and Ki67 in a single breast cancer cell indicates a favorable prognosis in ER-positive breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-01-08.

Abstract PO4-06-08: ZP4 AS A NOVEL TARGET FOR CAR T CELL THERAPY IN TRIPLE NEGATIVE BREAST CANCER

Abstract Triple negative breast cancer (TNBC) has the worst prognosis of BC subtypes, largely due to lack of approved targeted therapies. Chimeric antigen receptor (CAR) T cells have demonstrated great success in certain hematological malignancies; however, in the treatment of solid cancers, CAR T cells are faced with a variety of obstacles that limit their efficacy, including on-target/off-tumor toxicity. To minimize these toxicities, the ideal CAR T cell target must be overexpressed by the tumor and absent from vital organs. Cancer/germline (CG) antigens satisfy this need, as their expression is restricted to male or female germ cells. Using a bioinformatic pipeline to identify novel CG antigens expressed in TNBC and other solid cancers, we have identified zona pellucida glycoprotein 4 (ZP4) as a candidate CG antigen target for CAR T cell therapy. This protein is a component of the human zona pellucida matrix, an extracellular structure that surrounds the oocyte and functions in folliculogenesis, species-specific fertilization, and early development. We have identified ZP4 expression in approximately 10% of TNBC cases from available RNAseq and proteomic databases and have confirmed ZP4 expression in several TNBC PDX models. The overall purpose of this study is to redirect T cells against ZP4 by engineering and validating a second generation ZP4-specific CAR. We have generated a library of monoclonal antibody (mAb) candidates against the extracellular portion of human ZP4. Antibody clones were screened, and their specificity validated via ELISA and flow cytometry, and the three strongest binders (z108, z128, and z164) were selected for further investigation. By IHC, we confirmed that the ZP4 mAb clones stained the area surrounding normal oocytes and did not show binding to any of the 23 normal tissues screened. The variable regions of the antibody heavy and light chains were sequenced using 5’RACE and used to assemble second generation CAR constructs composed of the variable heavy and light chain fragments separated by a linker, a CH2/CH3 hinge domain, a CD28 transmembrane domain, a CD28 co-stimulatory domain, and the CD3z signaling domain. Activated T cells transduced with retroviral supernatant express the ZP4 CAR constructs at high levels. While all ZP4 CAR T cells demonstrate antigen-specific cytotoxic killing of ZP4+ target tumor cells in short-term in vitro assays, z128 ZP4 CAR T cells demonstrate superior persistence and efficacy in long-term repeat tumor challenge in vitro assays and orthotopic in vivo mouse models. In summary, ZP4 is a promising target for TNBC and we have successfully engineered ZP4 specific CAR T cells. ZP4 CAR T cells effectively target and kill ZP4+ cells in in vitro cytotoxicity assays but perform differently in repeat tumor challenge assays and in vivo. Future studies will elucidate the precise differences between our three candidate CAR constructs and further test the effector function, trafficking, proliferation, and persistence of z128 ZP4 CAR T cells in vivo using ZP4+ PDX models. This work has exciting potential to bring a novel CAR T cell therapy to patients with TNBC, without concerns for on-target off-tumor toxicity. Citation Format: Lauren Somes, Jonathan Lei, Paul Shafer, Xinpei Yi, Diego Chamorro, Emily Madaras, Michael Lewis, Bing Zhang, Valentina Hoyos. ZP4 AS A NOVEL TARGET FOR CAR T CELL THERAPY IN TRIPLE NEGATIVE BREAST CANCER [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-06-08.

Abstract PO2-14-12: Accurate quantification of slide-level HER2 scores in breast cancer using a machine-learning model, AIM-HER2 Breast Cancer

Abstract Background: HER2 expression level is a key factor in determining the optimal treatment course for breast cancer patients. Roughly 15% of breast cancers are HER2(+), and determination of HER2 status is routinely assessed by immunohistochemistry (IHC). Accurate assessment of the HER2 IHC score (0, 1+, 2+, 3+) by pathologists is therefore critical, especially in light of novel therapeutic approaches demonstrating efficacy in the HER2-low setting (IHC scores 1+, and 2+/FISH-)1,2. To assist pathologists with the consistent provision of reproducible and accurate scores across the entire HER2 scoring range, we developed a machine-learning model (“AIM-HER2”) to generate accurate, slide-level HER2 scores aligned with ASCO-CAP guidelines in clinical breast cancer HER2 IHC specimens. Methods: AIM-HER2 was developed using whole-slide images (WSI; N=4261) from clinical and commercial sources. WSI were split into training (N=2694, 63%) and optimization (N=1567, 37%) sets. An additive multiple instance learning (aMIL) model3 was trained to predict HER2 scores directly from WSI and create interpretable heatmaps that depict HER2 predictions in tissue images. Image artifacts and in situ carcinomas were identified using previously trained artifact and tissue segmentation models and were excluded, leaving only regions of invasive carcinoma to be analyzed. AIM-HER2 performance was assessed on additional slides obtained from five academic or commercial sources (N=804 total, 770 evaluable) on which HER2 IHC was performed. Board-certified pathologists (N=52) with relevant experience provided manual HER2 scores based on ASCO-CAP guidelines. Nested pairwise non-inferiority analysis4 was used to compare model performance to that of pathologists (N=3 pathologists per slide). In the nested pairwise framework, agreement among pathologists was compared to agreement between AIM-HER2 and pathologists via linear kappa, so that summary metrics account for inter-pathologist variability. Results: High concordance was observed between AIM-HER2-predicted and pathologist-labeled slide-level HER2 scores, both overall and for each scoring level. Similar results were observed when assessing AIM-HER2 performance on multiple slide scanners and after IHC with multiple HER2 IHC antibody clones. Results are summarized in Table 1. Conclusions: We developed AIM-HER2, a novel aMIL-based approach for predicting slide-level HER2 IHC scores. AIM-HER2 has similar levels of agreement with pathologists as pathologists have with each other for determining HER2 score. This result is upheld when slides imaged using multiple scanning platforms and stained using multiple HER2 antibody clones. The performance of AIM-HER2 on multiple scanners and after multiple assays supports broad applicability of this algorithm in clinical laboratories, including for the identification of HER2-low cases. Work is ongoing to perform similar analyses in an independent, real-world dataset.

Abstract PO4-26-01: Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine

Abstract While targeted cancer therapies often rely on subjective and semi-quantitative visual assessment of protein biomarkers by pathologists through immunohistochemically stained tissue, the transformative force of computational pathology is reshaping healthcare by unleashing unprecedented diagnostic accuracy and unlocking personalized treatments. In recent years, we have established a large integrated computational pathology unit to foster collaboration between interdisciplinary teams of computer scientists, pathologists, molecular biologists, and data scientists. This integration of cutting-edge technologies enabled us to develop a computational pathology approach called Quantitative Continuous Scoring (QCS). QCS deploys the power of Deep Learning (DL) to provide objective and continuous expression data of biomarkers in digitized IHC whole slide images (WSI), particularly of proteins expressed at low levels. While manual scoring of IHC WSIs is limited by subjectivity and semi-quantitative assessment of protein expression, QCS overcomes these limitations with an unprecedented accuracy. QCS utilizes two DL-based algorithms, which we developed fully supervised by using pathologist input as the reference standard. These algorithms identify invasive tumour areas and segment each tumour cell across the WSI into cell nuclei, cytoplasm and membrane. Based on an accurate subcellular segmentation, we can compute biomarker expression, on a continuous scale, as mean Optical Density (OD) in each subcellular compartment based on the Hue-Saturation-Density (HSD) model. Therefore, this approach enables precise detection of the low biomarker expression range with single-cell resolution. Importantly, it also allows the computation of the spatial distribution of tumour cells across the WSI. We have successfully used QCS to drive the selection of antibody clones for IHC assays and to delineate the mode of action and PK/PD mechanisms. Of note, the combination of assessing continuous target expression and capturing the spatial distribution of tumor cells has provided surrogate markers to predict potential bystander activity of antibody drug conjugates (ADCs). This approach outperformed traditional pathologist scoring in identifying patient populations having maximum treatment benefit through retrospective analysis of multiple clinical trials. At present, all computational pathology approaches are developed based on conventional IHC assays that have been optimized for manual scoring. Importantly, we draw a vision in which the assay serves as a critical catalyst for unleashing the full potential of computational pathology by providing high-quality, standardized data inputs. We suggest an approach utilizing orthogonal methods as a reference standard to develop highly sensitive IHC assays, capable of detecting even subtle molecular and cellular changes with precision and exhibiting exceptional specificity for accurately identifying and distinguishing target biomarkers from background noise. In summary, we here describe and discuss a computational pathology-based approach for precise biomarker quantification and superior patient selection with broad applicability and the potential to transform the very fabric of how we diagnose and treat cancer. Citation Format: Mark Gustavson, Markus Schick, Ansh Kapil, Anatoliy Shumilov, Carl Barrett, Hadassah Sade. Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-01.

Abstract PO4-26-07: HER2-low prevalence in early breast cancer (BC) across reference laboratories in Brazil: potential impact of immunohistochemistry (IHC) antibody assay sensitivity

Abstract Background: Current definition of HER2-positive and HER2-low BC follows ASCO/CAP guidelines using IHC and/or in situ hybridization (ISH)-based techniques. Although there is no recommendation for a specific antibody assay, the companion diagnostic test for trastuzumab deruxtecan in the USA is Ventana PATHWAY anti-HER2 monoclonal antibody (4B5) run on Benchmark Ultra instrument. In this study, we assessed the prevalence of HER2-low BC in samples stained with Dako anti-HER2 polyclonal antibody (A0485) and analyzed with Autostainer Link 48 Agilent/Dako, commonly used in different large-volume laboratories in Brazil. Methods: Retrospective study of all early-stage BC samples without exposure to neoadjuvant therapy tested for HR plus HER2 status in Oncoclínicas Precision Medicine (Locus Lab) from 2021 to 2023 and analyzed following ASCO/CAP guidelines. Tumors with HER2 IHC score 0 were classified as HER2-zero, whereas tumors with HER2 score 1+ and those with HER2 score 2+ with ISH-negative were classified as HER2-low. To assess the impact of preanalytical factors on HER2-low positivity, we stratified samples as in-house (part of Oncoclínicas network) or external (other institutions’ FFPE preparation conditions not controlled). Results were also validated in independent IRA Lab using the same Dako anti-HER2 polyclonal antibody (A0485) on Autostainer Link 48 Agilent/Dako. Results: Out of 1,638 eligible samples from Locus Lab, 84% were classified as HR-positive/HER2 negative, 12% HER2-positive, and 4% triple-negative. In 1,386 HR-positive/HER2 negative samples, 83% were HER2-zero, and 17% (CI95% 15%-19%) were HER2-low (1+ in 79% and 2+ with ISH negative in 21%). In 70 triple-negative samples, 62% were HER2-zero and 38% (CI95% 27%-51%) were HER2-low (1+ in 44% and 2+ with ISH negative in 56%). HER2-low positivity was 17% in the subset of in-house samples (N=1.090) and 16% in external referrals (P=0.41). In the independent cohort, out of 441 samples from IRA Lab, 80% were HR-positive/HER2 negative, 12% HER2-positive and 8% triple negative. In 352 HR positive/HER2 negative samples, 80% were HER2-zero and 20% (CI95% 16%-25%) were HER2-low. In 36 triple-negative samples, 72% were HER2-zero and 28% (CI95% 14%-45%) were HER2-low. Conclusions: Different from another Brazilian cohort where the prevalence of HER2-low was 50% with monoclonal anti-HER2 antibodies (Reinert et al., SABCS 2020), our data suggests that the reduced proportion of samples with HER2-low status may be related to antibody clone sensitivity and not linked to preanalytical factors or local ancestry/cancer biology. Indeed, a recent Italian cohort also had lower than expected prevalence of HER2-low in surgical specimens using anti-HER2 Dako A0485 assay on Omnis instrument (Rossi et al., Breast Cancer Res Treat 2023). Prior studies have found differential analytical sensitivity of antibodies for HER2-low status, while HER2 score 3+ detection is equivalent (Ruschoff et al., Virchows Archiv 2022). We recommend prospective evaluation of the HER2-low status with companion-diagnostic Ventana 4B5 assay and alternative antibodies and instruments. Citation Format: Leonard M da Silva, Fernanda Orpinelli Rego, Matheus Costa e Silva, Tomas Reinert, Fernanda Koyama, Daniel Bueno da Cunha, Vagner Duarte, Emílio Pereira, Bruno Ferrari, Rodrigo Dienstmann. HER2-low prevalence in early breast cancer (BC) across reference laboratories in Brazil: potential impact of immunohistochemistry (IHC) antibody assay sensitivity [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-07.

SIGLEC-3 (CD33) serves as an effective target in tumor progression

Abstract Human CD33 (Siglec-3) possesses an immune-receptor tyrosine-based inhibition motif (ITIM), which recruits Src homology 2 (SH2) containing phosphatases (SHP-1/2) and inositol phosphatase (SHIP) and exerts inhibitory effects. The structure and downstream signaling of CD33 bear similarity to programmed cell death protein-1 (PD-1), a promising target in cancer immune therapy. Previous studies indicate that CD33 serves as a therapeutic target in acute myeloid leukemia (AML), additionally, CD33 also acts as a prevalent surface marker of human myeloid-derived suppressor cells (MDSCs). According to the inhibitory signaling upon CD33 activation, CD33 may participate in tumor progression and the regulatory role of CD33 in solid tumors is still unclear. To investigate whether CD33 influences cancer progression, we established a melanoma tumor (B16F10) mouse model in monocyte/macrophage-specific human CD33 transgenic mice (hCD33 Tg mice, Cx3cr1cre/-hCD33M+/-). Compared to wild-type mice (WT), tumor growth and mortality were larger and higher in CD33 Tg mice. Moreover, an antagonistic anti-hCD33 monoclonal antibody (clone 4L3-46) treatment successfully attenuated tumor growth in hCD33 Tg mice and led to a restructuring of the infiltrating MDSCs population. These results indicate that human CD33 contributes to the advancement of tumors, and the blockade of CD33 represents a promising strategy in tumor therapy.