Physics-driven structural docking and protein language models accelerate antibody screening and design for broad-spectrum antiviral therapy.

Therapeutic antibodies have become one of the most influential therapeutics in modern medicine to fight against infectious pathogens, cancer, and many other diseases. However, experimental screening for highly efficacious targeting antibodies is labor-intensive and of high cost, which is exacerbated by evolving antigen targets under selective pressure such as fast-mutating viral variants. As a proof-of-concept, we developed a machine learning-assisted antibody generation pipeline that greatly accelerates the screening and re-design of immunoglobulins G (IgGs) against a broad spectrum of SARS-CoV-2 coronavirus variant strains. These viruses infect human host cells via the viral spike protein binding to the host cell receptor angiotensin-converting enzyme 2 (ACE2). Using over 1300 IgG sequences derived from convalescent patient B cells that bind with spike's receptor binding domain (RBD), we first established protein structural docking models in assessing the RBD-IgG-ACE2 interaction interfaces and predicting the virus-neutralizing activity of each IgG with a confidence score. Additionally, employing Gaussian process regression (also known as Kriging) in a latent space of an antibody language model, we predicted the landscape of IgGs' activity profiles against individual coronaviral variants of concern. With functional analyses and experimental validations, we efficiently prioritized IgG candidates for neutralizing a broad spectrum of viral variants (wildtype, Delta, and Omicron) to prevent the infection of host cells in vitro and hACE2 transgenic mice in vivo. Furthermore, the computational analyses enabled rational redesigns of selective IgG clones with single amino acid substitutions at the RBD-binding interface to improve the IgG blockade efficacy for one of the severe, therapy-resistant strains - Delta (B.1.617). Our work expedites applications of artificial intelligence in antibody screening and re-design even in low-data regimes combining protein language models and Kriging for antibody sequence analysis, activity prediction, and efficacy improvement, in synergy with physics-driven protein docking models for antibody-antigen interface structure analyses and functional optimization.

Dynamic Glycoprotein Hyposialylation Promotes Chemotherapy Evasion and Metastatic Seeding of Quiescent Circulating Tumor Cell Clusters in Breast Cancer.

Most circulating tumor cells (CTC) are detected as single cells, whereas a small proportion of CTCs in multicellular clusters with stemness properties possess 20- to 100-times higher metastatic propensity than the single cells. Here we report that CTC dynamics in both singles and clusters in response to therapies predict overall survival for breast cancer. Chemotherapy-evasive CTC clusters are relatively quiescent with a specific loss of ST6GAL1-catalyzed α2,6-sialylation in glycoproteins. Dynamic hyposialylation in CTCs or deficiency of ST6GAL1 promotes cluster formation for metastatic seeding and enables cellular quiescence to evade paclitaxel treatment in breast cancer. Glycoproteomic analysis reveals newly identified protein substrates of ST6GAL1, such as adhesion or stemness markers PODXL, ICAM1, ECE1, ALCAM1, CD97, and CD44, contributing to CTC clustering (aggregation) and metastatic seeding. As a proof of concept, neutralizing antibodies against one newly identified contributor, PODXL, inhibit CTC cluster formation and lung metastasis associated with paclitaxel treatment for triple-negative breast cancer. SIGNIFICANCE: This study discovers that dynamic loss of terminal sialylation in glycoproteins of CTC clusters contributes to the fate of cellular dormancy, advantageous evasion to chemotherapy, and enhanced metastatic seeding. It identifies PODXL as a glycoprotein substrate of ST6GAL1 and a candidate target to counter chemoevasion-associated metastasis of quiescent tumor cells. This article is featured in Selected Articles from This Issue, p. 1949.

Unique molecular signatures sustained in circulating monocytes and regulatory T cells in convalescent COVID-19 patients.

Over two years into the COVID-19 pandemic, the human immune response to SARS-CoV-2 during the active disease phase has been extensively studied. However, the long-term impact after recovery, which is critical to advance our understanding SARS-CoV-2 and COVID-19-associated long-term complications, remains largely unknown. Herein, we characterized single-cell profiles of circulating immune cells in the peripheral blood of 100 patients, including convalescent COVID-19 and sero-negative controls. Flow cytometry analyses revealed reduced frequencies of both short-lived monocytes and long-lived regulatory T (Treg) cells within the patients who have recovered from severe COVID-19. sc-RNA seq analysis identifies seven heterogeneous clusters of monocytes and nine Treg clusters featuring distinct molecular signatures in association with COVID-19 severity. Asymptomatic patients contain the most abundant clusters of monocytes and Tregs expressing high CD74 or IFN-responsive genes. In contrast, the patients recovered from a severe disease have shown two dominant inflammatory monocyte clusters featuring S100 family genes: one monocyte cluster of S100A8 & A9 coupled with high HLA-I and another cluster of S100A4 & A6 with high HLA-II genes, a specific non-classical monocyte cluster with distinct IFITM family genes, as well as a unique TGF-ß high Treg Cluster. The outpatients and seronegative controls share most of the monocyte and Treg clusters patterns with high expression of HLA genes. Surprisingly, while presumably short-lived monocytes appear to have sustained alterations over 4 months, the decreased frequencies of long-lived Tregs (high HLA-DRA and S100A6) in the outpatients restore over the tested convalescent time (≥ 4 months). Collectively, our study identifies sustained and dynamically altered monocytes and Treg clusters with distinct molecular signatures after recovery, associated with COVID-19 severity.

Machine learning-assisted elucidation of CD81-CD44 interactions in promoting cancer stemness and extracellular vesicle integrity.

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

Unique molecular signatures sustained in circulating monocytes and regulatory T cells in Convalescent COVID-19 patients.

Over two years into the COVID-19 pandemic, the human immune response to SARS-CoV-2 during the active disease phase has been extensively studied. However, the long-term impact after recovery, which is critical to advance our understanding SARS-CoV-2 and COVID-19-associated long-term complications, remains largely unknown. Herein, we characterized multi-omic single-cell profiles of circulating immune cells in the peripheral blood of 100 patients, including covenlesent COVID-19 and sero-negative controls. The reduced frequencies of both short-lived monocytes and long-lived regulatory T (Treg) cells are significantly associated with the patients recovered from severe COVID-19. Consistently, sc-RNA seq analysis reveals seven heterogeneous clusters of monocytes (M0-M6) and ten Treg clusters (T0-T9) featuring distinct molecular signatures and associated with COVID-19 severity. Asymptomatic patients contain the most abundant clusters of monocyte and Treg expressing high CD74 or IFN-responsive genes. In contrast, the patients recovered from a severe disease have shown two dominant inflammatory monocyte clusters with S100 family genes: S100A8 & A9 with high HLA-I whereas S100A4 & A6 with high HLA-II genes, a specific non-classical monocyte cluster with distinct IFITM family genes, and a unique TGF-ß high Treg Cluster. The outpatients and seronegative controls share most of the monocyte and Treg clusters patterns with high expression of HLA genes. Surprisingly, while presumably short-ived monocytes appear to have sustained alterations over 4 months, the decreased frequencies of long-lived Tregs (high HLA-DRA and S100A6) in the outpatients restore over the tested convalescent time (>= 4 months). Collectively, our study identifies sustained and dynamically altered monocytes and Treg clusters with distinct molecular signatures after recovery, associated with COVID-19 severity.

Circulating ACE2-expressing extracellular vesicles block broad strains of SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the pandemic of the coronavirus induced disease 2019 (COVID-19) with evolving variants of concern. It remains urgent to identify novel approaches against broad strains of SARS-CoV-2, which infect host cells via the entry receptor angiotensin-converting enzyme 2 (ACE2). Herein, we report an increase in circulating extracellular vesicles (EVs) that express ACE2 (evACE2) in plasma of COVID-19 patients, which levels are associated with severe pathogenesis. Importantly, evACE2 isolated from human plasma or cells neutralizes SARS-CoV-2 infection by competing with cellular ACE2. Compared to vesicle-free recombinant human ACE2 (rhACE2), evACE2 shows a 135-fold higher potency in blocking the binding of the viral spike protein RBD, and a 60- to 80-fold higher efficacy in preventing infections by both pseudotyped and authentic SARS-CoV-2. Consistently, evACE2 protects the hACE2 transgenic mice from SARS-CoV-2-induced lung injury and mortality. Furthermore, evACE2 inhibits the infection of SARS-CoV-2 variants (α, ß, and δ) with equal or higher potency than for the wildtype strain, supporting a broad-spectrum antiviral mechanism of evACE2 for therapeutic development to block the infection of existing and future coronaviruses that use the ACE2 receptor.

ICAM1 initiates CTC cluster formation and trans-endothelial migration in lung metastasis of breast cancer.

Circulating tumor cell (CTC) clusters mediate metastasis at a higher efficiency and are associated with lower overall survival in breast cancer compared to single cells. Combining single-cell RNA sequencing and protein analyses, here we report the profiles of primary tumor cells and lung metastases of triple-negative breast cancer (TNBC). ICAM1 expression increases by 200-fold in the lung metastases of three TNBC patient-derived xenografts (PDXs). Depletion of ICAM1 abrogates lung colonization of TNBC cells by inhibiting homotypic tumor cell-tumor cell cluster formation. Machine learning-based algorithms and mutagenesis analyses identify ICAM1 regions responsible for homophilic ICAM1-ICAM1 interactions, thereby directing homotypic tumor cell clustering, as well as heterotypic tumor-endothelial adhesion for trans-endothelial migration. Moreover, ICAM1 promotes metastasis by activating cellular pathways related to cell cycle and stemness. Finally, blocking ICAM1 interactions significantly inhibits CTC cluster formation, tumor cell transendothelial migration, and lung metastasis. Therefore, ICAM1 can serve as a novel therapeutic target for metastasis initiation of TNBC.

EGFR inhibition blocks cancer stem cell clustering and lung metastasis of triple negative breast cancer.

Triple-negative breast cancer (TNBC) is one of the most aggressive and metastatic breast cancer subtypes lacking targeted therapy. Our recent work demonstrated that circulating tumor cell (CTC) clusters and polyclonal metastasis of TNBC are driven by aggregation of CD44+ cancer stem cells (CSC) and associated with an unfavorable prognosis, such as low overall survival. However, there is no existing therapeutic that can specifically block CTC or CSC cluster formation. Methods: Using patient-derived xenograft (PDX) models, we established an ex vivo tumor cell clustering assay for a pilot screening of blockade antibodies. After identifying EGFR as a target candidate, we modulated the gene expression and inhibited its kinase activity to determine its functional importance in tumor cell clustering and therapeutic inhibition of lung metastasis. We also examined the molecular regulation network of EGFR and a potential connection to CSC marker CD44 and microRNAs, which regulate CTC clustering. Results: We report here that EGFR inhibition successfully blocks circulating CSC (cCSC) clustering and lung metastasis of TNBC. EGFR enhances CD44-mediated tumor cell aggregation and CD44 stabilizes EGFR. Importantly, blocking EGFR by a novel anti-EGFR monoclonal antibody (clone LA1) effectively blocked cell aggregation in vitro and reduced lung metastasis in vivo. Furthermore, our data demonstrated that the tumor suppressor microRNA-30c serves as another negative regulator of cCSC clustering and lung metastasis by targeting CD44 as well as its downstream effector EGFR. Conclusion: Our studies identify a novel anti-EGFR therapeutic strategy to inhibit cCSC aggregation and therefore abolish cCSC cluster-mediated metastasis of TNBC.

Dose-dependent reproductive toxicity of sodium benzoate in male rats: Inflammation, oxidative stress and apoptosis.

The synthetic food preservative sodium benzoate (SB) is widely used in both food and pharmaceutical industries. A growing body of evidence highlights the adverse effects of SB on human health; however, effect of the prolonged intake of SB on the reproductive system is not fully elucidated. The current study investigates the effect of different doses of SB (0-1000 mg/kg BW) on the reproductive system of male rats administered oral SB for 90 consecutive days. Results revealed that increasing doses of SB significantly altered the weight of reproductive organs, decreased sperm count and motility and enhanced the percentage of abnormal sperms. This was concomitant with significant decline in plasma testosterone and FSH levels, increase in plasma LH and decrease in the activities of 17ß-HSD and 17-KSR enzymes in the testes. Inflammation and oxidative stress were induced as indicated by the significant increase in TNF-α and IL-6 levels, inhibition of antioxidant enzymes activity and levels of GSH, increase in the levels of NO and TBARS and enhanced protein expression of mtTFA and UCP2 in the testes. Interestingly, p53 expression and caspase-3 activity were upregulated in the testes suggesting induction of apoptosis. Histopathological examination of the testes confirmed apoptosis and revealed degenerative alterations of the testes' architecture and perturbation of spermatogenesis. Based upon these findings, the no-observed-adverse-effect level of SB on the reproductive system was determined to be less than 1 mg/kg BW/day, highlighting the risks of long-term exposure to low as well as high doses of SB on male reproductive health.

Mathematical Modelling for the Role of CD4+T Cells in Tumor-Immune Interactions.

Mathematical modelling has been used to study tumor-immune cell interaction. Some models were proposed to examine the effect of circulating lymphocytes, natural killer cells, and CD8+T cells, but they neglected the role of CD4+T cells. Other models were constructed to study the role of CD4+T cells but did not consider the role of other immune cells. In this study, we propose a mathematical model, in the form of a system of nonlinear ordinary differential equations, that predicts the interaction between tumor cells and natural killer cells, CD4+T cells, CD8+T cells, and circulating lymphocytes with or without immunotherapy and/or chemotherapy. This system is stiff, and the Runge-Kutta method failed to solve it. Consequently, the "Adams predictor-corrector" method is used. The results reveal that the patient's immune system can overcome small tumors; however, if the tumor is large, adoptive therapy with CD4+T cells can be an alternative to both CD8+T cell therapy and cytokines in some cases. Moreover, CD4+T cell therapy could replace chemotherapy depending upon tumor size. Even if a combination of chemotherapy and immunotherapy is necessary, using CD4+T cell therapy can better reduce the dose of the associated chemotherapy compared to using combined CD8+T cells and cytokine therapy. Stability analysis is performed for the studied patients. It has been found that all equilibrium points are unstable, and a condition for preventing tumor recurrence after treatment has been deduced. Finally, a bifurcation analysis is performed to study the effect of varying system parameters on the stability, and bifurcation points are specified. New equilibrium points are created or demolished at some bifurcation points, and stability is changed at some others. Hence, for systems turning to be stable, tumors can be eradicated without the possibility of recurrence. The proposed mathematical model provides a valuable tool for designing patients' treatment intervention strategies.

The Arabian camel, Camelus dromedarius interferon epsilon: Functional expression, in vitro refolding, purification and cytotoxicity on breast cancer cell lines.

The current study highlights, for the first time, cloning, overexpression and purification of the novel interferon epsilon (IFNƐ), from the Arabian camel Camelus dromedaries. The study then assesses the cytotoxicity of IFNε against two human breast cancer cell lines MDA-MB-231 and MCF-7. Full-length cDNA encoding interferon epsilon (IFNε) was isolated and cloned from the liver of the Arabian camel, C. dromedarius using reverse transcription-polymerase chain reaction. The sequence analysis of the camel IFNε cDNA showed a 582-bp open reading frame encoding a protein of 193 amino acids with an estimated molecular weight of 21.230 kDa. A BLAST search analysis revealed that the C. dromedarius IFNε shared high sequence identity with the IFN genes of other species, such as Camelus ferus, Vicugna pacos, and Homo sapiens. Expression of the camel IFNε cDNA in Escherichia coli gave a fusion protein band of 24.97 kDa after induction with either isopropyl ß-D-1-thiogalactopyranoside or lactose for 5 h. Recombinant IFNε protein was overexpressed in the form of inclusion bodies that were easily solubilized and refolded using SDS and KCl. The solubilized inclusion bodies were purified to apparent homogeneity using nickel affinity chromatography. We examined the effect of IFNε on two breast cancer cell lines MDA-MB-231 and MCF-7. In both cell lines, IFNε inhibited cell survival in a dose dependent manner as observed by MTT assay, morphological changes and apoptosis assay. Caspase-3 expression level was found to be increased in MDA-MB-231 treated cells as compared to untreated cells.

Coactivation of Estrogen Receptor and IKKß Induces a Dormant Metastatic Phenotype in ER-Positive Breast Cancer.

A growing body of evidence suggests that the inflammatory NFκB pathway is associated with the progression of ER+ tumors to more aggressive stages. However, it is unknown whether NFκB is a driver or a consequence of aggressive ER+ disease. To investigate this question, we developed breast cancer cell lines expressing an inducible, constitutively active form of IκB kinase ß (CA-IKKß), a key kinase in the canonical NFκB pathway. We found that CA-IKKß blocked E2-dependent cell proliferation in vitro and tumor growth in vivo in a reversible manner, suggesting that IKKß may contribute to tumor dormancy and recurrence of ER+ disease. Moreover, coactivation of ER and IKKß promoted cell migration and invasion in vitro and drove experimental metastasis in vivo Gene expression profiling revealed a strong association between ER and CA-IKKß-driven gene expression and clinically relevant invasion and metastasis gene signatures. Mechanistically, the invasive phenotype appeared to be driven by an expansion of a basal/stem-like cell population rather than EMT. Taken together, our findings suggest that coactivation of ER and the canonical NFκB pathway promotes a dormant, metastatic phenotype in ER+ breast cancer and implicates IKKß as a driver of certain features of aggressive ER+ breast cancer.Significance: The canonical NFκB pathway promotes expansion of stem/basal-like cells and a dormant, metastatic phenotype in ER+ breast cancer cells. Cancer Res; 78(4); 974-84. ©2017 AACR.

Dimethyl Fumarate Inhibits the Nuclear Factor κB Pathway in Breast Cancer Cells by Covalent Modification of p65 Protein.

In breast tumors, activation of the nuclear factor κB (NFκB) pathway promotes survival, migration, invasion, angiogenesis, stem cell-like properties, and resistance to therapy--all phenotypes of aggressive disease where therapy options remain limited. Adding an anti-inflammatory/anti-NFκB agent to breast cancer treatment would be beneficial, but no such drug is approved as either a monotherapy or adjuvant therapy. To address this need, we examined whether dimethyl fumarate (DMF), an anti-inflammatory drug already in clinical use for multiple sclerosis, can inhibit the NFκB pathway. We found that DMF effectively blocks NFκB activity in multiple breast cancer cell lines and abrogates NFκB-dependent mammosphere formation, indicating that DMF has anti-cancer stem cell properties. In addition, DMF inhibits cell proliferation and significantly impairs xenograft tumor growth. Mechanistically, DMF prevents p65 nuclear translocation and attenuates its DNA binding activity but has no effect on upstream proteins in the NFκB pathway. Dimethyl succinate, the inactive analog of DMF that lacks the electrophilic double bond of fumarate, is unable to inhibit NFκB activity. Also, the cell-permeable thiol N-acetyl l-cysteine, reverses DMF inhibition of the NFκB pathway, supporting the notion that the electrophile, DMF, acts via covalent modification. To determine whether DMF interacts directly with p65, we synthesized and used a novel chemical probe of DMF by incorporating an alkyne functionality and found that DMF covalently modifies p65, with cysteine 38 being essential for the activity of DMF. These results establish DMF as an NFκB inhibitor with anti-tumor activity that may add therapeutic value in the treatment of aggressive breast cancers.

NFκB affects estrogen receptor expression and activity in breast cancer through multiple mechanisms.

Estrogen receptor (ER) and NFκB are two widely expressed, pleiotropic transcription factors that have been shown to interact and affect one another's activity. While the ability of ER to repress NFκB activity has been extensively studied and is thought to underlie the anti-inflammatory activity of estrogens, how NFκB signaling affects ER activity is less clear. This is a particularly important question in breast cancer since activation of NFκB in ER positive tumors is associated with failure of endocrine and chemotherapies. In this review, we provide an update on the multiple mechanisms by which NFκB can influence ER activity, including down-regulation of ER expression, enhanced ER recruitment to DNA, and increased transcriptional activity of both liganded and unliganded ER. Additionally, a novel example of NFκB potentiation of ER-dependent gene repression is reviewed. Together, these mechanisms can alter response to endocrine therapies and may underlie the poor outcome for women with ER positive tumors that have active NFκB signaling.

Growth hormone potentiates 17ß-estradiol-dependent breast cancer cell proliferation independently of IGF-I receptor signaling.

Estrogen action in mammary gland development and breast cancer progression is tightly linked to the GH/IGF-I axis. Although many of the effects of GH on mammary gland growth and development require IGF-I, the extent to which GH action in breast cancer depends on IGF-I is not known. We examined GH action in a panel of estrogen receptor-positive breast cancer cell lines and found that T47D cells express significant levels of GH receptor and that GH significantly enhances 17ß-estradiol (E2)-stimulated proliferation in these cells. GH action in the T47D cells was independent of changes in IGF-I and IGF-I receptor (IGF-IR) expression and IGF-IR signaling, suggesting that GH can exert direct effects on breast cancer cells. Although E2-dependent proliferation required IGF-IR signaling, the combination of GH+E2 overcame inhibition of IGF-IR activity to restore proliferation. In contrast, GH required both Janus kinase 2 and epidermal growth factor receptor signaling for subsequent ERK activation and potentiation of E2-dependent proliferation. Downstream of these pathways, we identified a number of immediate early-response genes associated with proliferation that are rapidly and robustly up-regulated by GH. These findings demonstrate that GH can have important effects in breast cancer cells that are distinct from IGF-IR activity, suggesting that novel drugs or improved combination therapies targeting estrogen receptor and the GH/IGF axis may be beneficial for breast cancer patients.

Cisplatin induced damage in kidney genomic DNA and nephrotoxicity in male rats: the protective effect of grape seed proanthocyanidin extract.

The clinical use of cisplatin is highly limited, because of its renal toxicity. In this study, the protective effect of grape seed proanthocyanidin extract (GSPE) against cisplatin-induced nephrotoxicity is investigated in rats. Results showed that DNA qualitative analysis indicated an increase in the instability of the DNA purified from the cisplatin exposed kidney cells. Agarose gel electrophoresis revealed DNA damage in the form of smearing as well as ladder like fragmentation of the kidney genomic DNA. Cisplatin produced different RAPD patterns compared to control. Deletion of bands for the amplified DNA extracted from cisplatin treated rats was the most common outcome. Treatment with cisplatin decreased albumin, and increased urea and creatinine. Cisplatin significantly increased the level of kidney free radicals, and decreased the glutathione content and the activities of the antioxidant enzymes. The presence of GSPE with cisplatin significantly alleviated its nephrotoxicity. In conclusion, the present study showed that cisplatin induced damage in the kidney genomic DNA, lipid peroxidation, inhibition of antioxidant enzymes and alterations of biochemical parameters in plasma and kidney of rats. While, GSPE treatment protected against the toxic effects induced by cisplatin. Thus, GSPE may be used to prevent toxicity during chemotherapeutic treatment with cisplatin.