Radiolabelling and preclinical characterisation of [89Zr]Zr-Df-ATG-101 bispecific to PD-L1/4-1BB.

PURPOSE: ATG-101, a bispecific antibody that simultaneously targets the immune checkpoint PD-L1 and the costimulatory receptor 4-1BB, activates exhausted T cells upon PD-L1 crosslinking. Previous studies demonstrated promising anti-tumour efficacy of ATG-101 in preclinical models. Here, we labelled ATG-101 with 89Zr to confirm its tumour targeting effect and tissue biodistribution in a preclinical model. We also evaluated the use of immuno-PET to study tumour uptake of ATG-101 in vivo. METHODS: ATG-101, anti-PD-L1, and an isotype control were conjugated with p-SCN-Deferoxamine (Df). The Df-conjugated antibodies were radiolabelled with 89Zr, and their radiochemical purity, immunoreactivity, and serum stability were assessed. We conducted PET/MRI and biodistribution studies on [89Zr]Zr-Df-ATG-101 in BALB/c nude mice bearing PD-L1-expressing MDA-MB-231 breast cancer xenografts for up to 10 days after intravenous administration of [89Zr]Zr-labelled antibodies. The specificity of [89Zr]Zr-Df-ATG-101 was evaluated through a competition study with unlabelled ATG-101 and anti-PD-L1 antibodies. RESULTS: The Df-conjugation and [89Zr]Zr -radiolabelling did not affect the target binding of ATG-101. Biodistribution and imaging studies demonstrated biological similarity of [89Zr]Zr-Df-ATG-101 and [89Zr]Zr-Df-anti-PD-L1. Tumour uptake of [89Zr]Zr-Df-ATG-101 was clearly visualised using small-animal PET imaging up to 7 days post-injection. Competition studies confirmed the specificity of PD-L1 targeting in vivo. CONCLUSION: [89Zr]Zr-Df-ATG-101 in vivo distribution is dependent on PD-L1 expression in the MDA-MB-231 xenograft model. Immuno-PET with [89Zr]Zr-Df-ATG-101 provides real-time information about ATG-101 distribution and tumour uptake in vivo. Our data support the use of [89Zr]Zr-Df-ATG-101 to assess tumour and tissue uptake of ATG-101.

Scientific figures interpreted by ChatGPT: strengths in plot recognition and limits in color perception.

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting basic bioinformatics data analyses. The recent feature of accepting image inputs by ChatGPT, also known as GPT-4V(ision), motivated us to explore its efficacy in deciphering bioinformatics scientific figures. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when color perception and quantitative analysis of visual elements were involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

Tumor targeted alpha particle therapy with an actinium-225 labelled antibody for carbonic anhydrase IX.

Selective antibody targeted delivery of α particle emitting actinium-225 to tumors has significant therapeutic potential. This work highlights the design and synthesis of a new bifunctional macrocyclic diazacrown ether chelator, H2MacropaSqOEt, that can be conjugated to antibodies and forms stable complexes with actinium-225. The macrocyclic diazacrown ether chelator incorporates a linker comprised of a short polyethylene glycol fragment and a squaramide ester that allows selective reaction with lysine residues on antibodies to form stable vinylogous amide linkages. This new H2MacropaSqOEt chelator was used to modify a monoclonal antibody, girentuximab (hG250), that binds to carbonic anhydrase IX, an enzyme that is overexpressed on the surface of cancers such as clear cell renal cell carcinoma. This new antibody conjugate (H2MacropaSq-hG250) had an average chelator to antibody ratio of 4 : 1 and retained high affinity for carbonic anhydrase IX. H2MacropaSq-hG250 was radiolabeled quantitatively with [225Ac]AcIII within one minute at room temperature with micromolar concentrations of antibody and the radioactive complex is stable in human serum for >7 days. Evaluation of [225Ac]Ac(MacropaSq-hG250) in a mouse xenograft model, that overexpresses carbonic anhydrase IX, demonstrated a highly significant therapeutic response. It is likely that H2MacropaSqOEt could be used to modify other antibodies providing a readily adaptable platform for other actinium-225 based therapeutics.

Biologics initiation in moderate versus severe rheumatoid arthritis: real-world experience from a Canadian registry.

OBJECTIVES: To evaluate the treat-to-target experience, and quality of life measures of moderate and severe rheumatoid arthritis (RA) patients initiating a biologic in a real-world setting of a publicly funded payer system. METHODS: Biologic naive RA patients who had initiated their first biologic while enrolled in the Ontario Best Practices Research Initiative registry from 2008 to 2020 were selected if they had moderate (DAS28 >3.2 to ≤5.1) or severe (DAS28 >5.1) RA. Remission, LDA, DAS28, HAQ-DI, fatigue, sleep, drug persistence and characteristics associated with remission were assessed at 12 months post biologic initiation. RESULTS: Overall, 838 patients initiated their first biologic, 264 had moderate RA and 219 had severe RA. After 12 months, 44% moderate RA vs. 21% severe RA achieved remission (p<0.0001), and 59% moderate RA vs. 35% severe RA reached LDA (p<0.0001). Mean change (SD) from baseline in DAS28 was 2.2 (1.5) in severe RA vs. 1.4 (1.3) in moderate RA (p<0.0001), in fatigue score was 1.11 (3.2) in severe RA vs. 0.98 (3.2) in moderate RA (p<0.0001). Moderate disease at a biologic initiation was positively associated with remission (p=0.0016). Female gender (p=0.0170), and a higher HAQ-DI score at baseline (p=0.0042) were negatively associated with remission. Biologic persistence was 77% for moderate, and 73% for severe (p=0.2444). CONCLUSIONS: Severe RA patients had higher mean score improvements in DAS28, sleep and fatigue. Moderate RA was more likely to reach remission or LDA. Both groups had similar biologic persistence at 12 months. These findings highlight the importance of the treat-to-target approach and its potential underutilisation in the real-world setting.

Bioinformatics Illustrations Decoded by ChatGPT: The Good, The Bad, and The Ugly.

Emerging studies underscore the promising capabilities of large language model-based chatbots in conducting fundamental bioinformatics data analyses. The recent feature of accepting image-inputs by ChatGPT motivated us to explore its efficacy in deciphering bioinformatics illustrations. Our evaluation with examples in cancer research, including sequencing data analysis, multimodal network-based drug repositioning, and tumor clonal evolution, revealed that ChatGPT can proficiently explain different plot types and apply biological knowledge to enrich interpretations. However, it struggled to provide accurate interpretations when quantitative analysis of visual elements was involved. Furthermore, while the chatbot can draft figure legends and summarize findings from the figures, stringent proofreading is imperative to ensure the accuracy and reliability of the content.

Preclinical radiolabeling, in vivo biodistribution and positron emission tomography of a novel pyrrolobenzodiazepine (PBD)-based antibody drug conjugate targeting ASCT2.

INTRODUCTION: Anti-ASCT2 antibody drug conjugate (ADC) MEDI7247 has been under development as a potential anti-cancer therapy for patients with selected relapsed/refractory hematological malignancies and advanced solid tumors by MedImmune. Although promising efficacy was observed in the clinic, pharmacokinetic (PK) analyses observed low exposure of MEDI7247 in phase I hematological patients. To investigate the biodistribution properties of MEDI7247, MEDI7247 and control antibodies were radiolabeled with zirconium-89 and in vitro and in vivo properties characterized. METHODS: MEDI7247 (human anti-ASCT2 antibody conjugated with pyrrolobenzodiazepine (PBD)) and MEDI7519 (MEDI7247 without PBD drug conjugate) and an isotype control antibody drug conjugate construct were conjugated with p-isothiocyanatobenzyl-deferoxamine (Df) and radiolabeled with zirconium-89. In vitro studies included determining the radiochemical purity, protein integrity, immunoreactivity (Lindmo analysis), apparent antigen binding affinity for ASCT2-positive cells by Scatchard analysis and serum stability of the radiolabeled immunoconjugates. In vivo studies included biodistribution and PET/MRI imaging studies of the radiolabeled immunoconjugates in an ASCT2-positive tumor model, HT-29 colorectal carcinoma xenografts. RESULTS: Conditions for the Df-conjugation and radiolabeling of antibody constructs were determined to produce active radioimmunoconjugates. In vivo biodistribution and whole body PET/MRI imaging studies of [89Zr]Zr-Df-MEDI7519 and [89Zr]Zr-Df-MEDI7247 radioimmunoconjugates in HT-29 colon carcinoma xenografts in BALB/c nude mice demonstrated specific tumor localization. However, more rapid blood clearance and non-specific localization in liver was observed for [89Zr]Zr-Df-MEDI7247 and [89Zr]Zr-Df-MEDI7519 compared to isotype control ADC. Except for liver and bone, other normal tissues demonstrated clearance reflecting the blood clearance for all three constructs and no other abnormal tissue uptake. CONCLUSIONS AND ADVANCES IN KNOWLEDGE: Preclinical biodistribution analyses of [89Zr]Zr-Df-MEDI7247 and [89Zr]Zr-Df-MEDI7519 showed the biodistribution pattern of anti-ASCT2 ADC MEDI7247 was similar to parental MEDI7519, and both antibodies showed specific tumor uptake compared to an isotype control ADC. This study highlights an important role nuclear medicine imaging techniques can play in early preclinical assessment of drug specificity as part of the drug development pipeline.

MicroRNA-Based Discovery of Biomarkers, Therapeutic Targets, and Repositioning Drugs for Breast Cancer.

Breast cancer treatment can be improved with biomarkers for early detection and individualized therapy. A set of 86 microRNAs (miRNAs) were identified to separate breast cancer tumors from normal breast tissues (n = 52) with an overall accuracy of 90.4%. Six miRNAs had concordant expression in both tumors and breast cancer patient blood samples compared with the normal control samples. Twelve miRNAs showed concordant expression in tumors vs. normal breast tissues and patient survival (n = 1093), with seven as potential tumor suppressors and five as potential oncomiRs. From experimentally validated target genes of these 86 miRNAs, pan-sensitive and pan-resistant genes with concordant mRNA and protein expression associated with in-vitro drug response to 19 NCCN-recommended breast cancer drugs were selected. Combined with in-vitro proliferation assays using CRISPR-Cas9/RNAi and patient survival analysis, MEK inhibitors PD19830 and BRD-K12244279, pilocarpine, and tremorine were discovered as potential new drug options for treating breast cancer. Multi-omics biomarkers of response to the discovered drugs were identified using human breast cancer cell lines. This study presented an artificial intelligence pipeline of miRNA-based discovery of biomarkers, therapeutic targets, and repositioning drugs that can be applied to many cancer types.

Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer.

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.

MicroRNA, mRNA, and Proteomics Biomarkers and Therapeutic Targets for Improving Lung Cancer Treatment Outcomes.

The majority of lung cancer patients are diagnosed with metastatic disease. This study identified a set of 73 microRNAs (miRNAs) that classified lung cancer tumors from normal lung tissues with an overall accuracy of 96.3% in the training patient cohort (n = 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (n = 375). Based on association with patient survival (n = 1016), 10 miRNAs were identified as potential tumor suppressors (hsa-miR-144, hsa-miR-195, hsa-miR-223, hsa-miR-30a, hsa-miR-30b, hsa-miR-30d, hsa-miR-335, hsa-miR-363, hsa-miR-451, and hsa-miR-99a), and 4 were identified as potential oncogenes (hsa-miR-21, hsa-miR-31, hsa-miR-411, and hsa-miR-494) in lung cancer. Experimentally confirmed target genes were identified for the 73 diagnostic miRNAs, from which proliferation genes were selected from CRISPR-Cas9/RNA interference (RNAi) screening assays. Pansensitive and panresistant genes to 21 NCCN-recommended drugs with concordant mRNA and protein expression were identified. DGKE and WDR47 were found with significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated molecular machinery, an inhibitor of PDK1/Akt BX-912, an anthracycline antibiotic daunorubicin, and a multi-targeted protein kinase inhibitor midostaurin were discovered as potential repositioning drugs for treating lung cancer. These findings have implications for improving lung cancer diagnosis, optimizing treatment selection, and discovering new drug options for better patient outcomes.

Automated radiosynthesis of [89Zr]Zr-DFOSq-Durvalumab for imaging of PD-L1 expressing tumours in vivo.

OBJECTIVES: 89Zr-labelled proteins are gaining importance in clinical research in a variety of diseases. To date, no clinical study has been reported that utilizes an automated approach for radiosynthesis of 89Zr-labelled radiopharmaceuticals. We aim to develop an automated method for the clinical production of 89Zr-labelled proteins and apply this method to Durvalumab, a monoclonal antibody targeting PD-L1 immune-checkpoint protein. PD-L1 expression is poorly understood and can be up-regulated over the course of chemo- and radiotherapy treatment. The ImmunoPET multicentre study aims to examine the dynamics of PD-L1 expression via 89Zr-Durvalumab PET imaging before, during, and after chemoradiotherapy. The developed automated technique will enable reproducible clinical production of [89Zr]Zr-DFOSq-Durvalumab for this study at three different sites. METHODS: Conjugation of Durvalumab to H3DFOSqOEt was optimized for optimal chelator-to-antibody ratio. Automated radiolabelling of H3DFOSq-Durvalumab with zirconium-89 was optimized on the disposable cassette based iPHASE technologies MultiSyn radiosynthesizer using a modified cassette. Activity losses were tracked using a dose calibrator and minimized by optimizing fluid transfers, reaction buffer, antibody formulation additives and pH. The biological profile of the radiolabelled antibody was confirmed in vivo in PD-L1+ (HCC827) and PD-L1- (A549) murine xenografts. Clinical process validation and quality control were performed at three separate study sites to satisfy clinical release criteria. RESULTS: H3DFOSq-Durvalumab with an average CAR of 3.02 was obtained. Radiolabelling kinetics in succinate (20 mM, pH 6) were significantly faster when compared to HEPES (0.5 M, pH 7.2) with >90 % conversion observed after 15 min. Residual radioactivity in the 89Zr isotope vial was reduced from 24 % to 0.44 % ± 0.18 % (n = 7) and losses in the reactor vial were reduced from 36 % ± 6 % (n = 4) to 0.82 % ± 0.75 % (n = 4) by including a surfactant in the reaction and formulation buffers. Overall process yield was 75 % ± 6 % (n = 5) and process time was 40 min. Typically, 165 MBq of [89Zr]Zr-DFOSq-Durvalumab with an apparent specific activity of 315 MBq/mg ± 34 MBq/mg (EOS) was obtained in a volume of 3.0 mL. At end-of-synthesis (EOS), radiochemical purity and protein integrity were always >99 % and >96 %, respectively, and dropped to 98 % and 65 % after incubation in human serum for 7 days at 37 °C. Immunoreactive fraction in HEK293/PD-L1 cells was 83.3 ± 9.0 (EOS). Preclinical in vivo data at 144 h p.i. showed excellent SUVmax in PD-L1+ tumour (8.32 ± 0.59) with a tumour-background ratio of 17.17 ± 3.96. [89Zr]Zr-DFOSq-Durvalumab passed all clinical release criteria at each study site and was deemed suitable for administration in a multicentre imaging trial. CONCLUSION: Fully automated production of [89Zr]Zr-DFOSq-Durvalumab for clinical use was achieved with minimal exposure to the operator. The cassette-based approach allows for consecutive productions on the same day and offers an alternative to currently used manual protocols. The method should be broadly applicable to other proteins and has the potential for clinical impact considering the growing number of clinical trials investigating 89Zr-labelled antibodies.

CD8 + T cell infiltration is associated with improved survival and negatively correlates with hypoxia in clear cell ovarian cancer.

Unlike other histological types of epithelial ovarian carcinoma, clear cell ovarian carcinoma (CCOC) has poor response to therapy. In many other carcinomas, expression of the hypoxia-related enzyme Carbonic anhydrase IX (CAIX) by cancer cells is associated with poor prognosis, while the presence of CD8 + tumor-infiltrating lymphocytes (TIL) is positively prognostic. We employed [18F]EF5-PET/CT imaging, transcriptome profiling, and spatially-resolved histological analysis to evaluate relationships between CAIX, CD8, and survival in CCOC. Tissue microarrays (TMAs) were evaluated for 218 cases in the Canadian COEUR study. Non-spatial relationships between CAIX and CD8 were investigated using Spearman rank correlation, negative binomial regression and gene set enrichment analysis. Spatial relationships at the cell level were investigated using the cross K-function. Survival analysis was used to assess the relationship of CAIX and CD8 with patient survival for 154 cases. CD8 + T cell infiltration positively predicted survival with estimated hazard ratio 0.974 (95% CI 0.950, 1000). The negative binomial regression analysis found a strong TMA effect (p-value < 0.0001). It also indicated a negative association between CD8 and CAIX overall (p-value = 0.0171) and in stroma (p-value = 0.0050) but not in tumor (p-value = 0.173). Examination of the spatial association between the locations of CD8 + T cells and CAIX cells found a significant amount of heterogeneity in the first TMA, while in the second TMA there was a clear signal indicating negative spatial association in stromal regions. These results suggest that hypoxia may contribute to immune exclusion, primarily mediated by effects in stroma.

Bromodomain and extraterminal protein-targeted probe enables tumour visualisation in vivo using positron emission tomography.

Bromodomain and extraterminal (BET) proteins, a family of epigenetic regulators, have emerged as important oncology drug targets. BET proteins have not been targeted for molecular imaging of cancer. Here, we report the development of a novel molecule radiolabelled with positron emitting fluorine-18, [18F]BiPET-2, and its in vitro and preclinical evaluation in glioblastoma models.

Multi-Omics Immune Interaction Networks in Lung Cancer Tumorigenesis, Proliferation, and Survival.

There are currently no effective biomarkers for prognosis and optimal treatment selection to improve non-small cell lung cancer (NSCLC) survival outcomes. This study further validated a seven-gene panel for diagnosis and prognosis of NSCLC using RNA sequencing and proteomic profiles of patient tumors. Within the seven-gene panel, ZNF71 expression combined with dendritic cell activities defined NSCLC patient subgroups (n = 966) with distinct survival outcomes (p = 0.04, Kaplan-Meier analysis). ZNF71 expression was significantly associated with the activities of natural killer cells (p = 0.014) and natural killer T cells (p = 0.003) in NSCLC patient tumors (n = 1016) using Chi-squared tests. Overexpression of ZNF71 resulted in decreased expression of multiple components of the intracellular intrinsic and innate immune systems, including dsRNA and dsDNA sensors. Multi-omics networks of ZNF71 and the intracellular intrinsic and innate immune systems were computed as relevant to NSCLC tumorigenesis, proliferation, and survival using patient clinical information and in-vitro CRISPR-Cas9/RNAi screening data. From these networks, pan-sensitive and pan-resistant genes to 21 NCCN-recommended drugs for treating NSCLC were selected. Based on the gene associations with patient survival and in-vitro CRISPR-Cas9, RNAi, and drug screening data, MEK1/2 inhibitors PD-198306 and U-0126, VEGFR inhibitor ZM-306416, and IGF-1R inhibitor PQ-401 were discovered as potential targeted therapy that may also induce an immune response for treating NSCLC.

Hub Genes in Non-Small Cell Lung Cancer Regulatory Networks.

There are currently no accurate biomarkers for optimal treatment selection in early-stage non-small cell lung cancer (NSCLC). Novel therapeutic targets are needed to improve NSCLC survival outcomes. This study systematically evaluated the association between genome-scale regulatory network centralities and NSCLC tumorigenesis, proliferation, and survival in early-stage NSCLC patients. Boolean implication networks were used to construct multimodal networks using patient DNA copy number variation, mRNA, and protein expression profiles. T statistics of differential gene/protein expression in tumors versus non-cancerous adjacent tissues, dependency scores in in vitro CRISPR-Cas9/RNA interference (RNAi) screening of human NSCLC cell lines, and hazard ratios in univariate Cox modeling of the Cancer Genome Atlas (TCGA) NSCLC patients were correlated with graph theory centrality metrics. Hub genes in multi-omics networks involving gene/protein expression were associated with oncogenic, proliferative potentials and poor patient survival outcomes (p < 0.05, Pearson's correlation). Immunotherapy targets PD1, PDL1, CTLA4, and CD27 were ranked as top hub genes within the 10th percentile in most constructed multi-omics networks. BUB3, DNM1L, EIF2S1, KPNB1, NMT1, PGAM1, and STRAP were discovered as important hub genes in NSCLC proliferation with oncogenic potential. These results support the importance of hub genes in NSCLC tumorigenesis, proliferation, and prognosis, with implications in prioritizing therapeutic targets to improve patient survival outcomes.

Opposing functions of circadian protein DBP and atypical E2F family E2F8 in anti-tumor Th9 cell differentiation.

Interleukin-9 (IL-9)-producing CD4+ T helper cells (Th9) have been implicated in allergy/asthma and anti-tumor immunity, yet molecular insights on their differentiation from activated T cells, driven by IL-4 and transforming growth factor-beta (TGF-ß), is still lacking. Here we show opposing functions of two transcription factors, D-binding protein (DBP) and E2F8, in controlling Th9 differentiation. Specifically, TGF-ß and IL-4 signaling induces phosphorylation of the serine 213 site in the linker region of the Smad3 (pSmad3L-Ser213) via phosphorylated p38, which is necessary and sufficient for Il9 gene transcription. We identify DBP and E2F8 as an activator and repressor, respectively, for Il9 transcription by pSmad3L-Ser213. Notably, Th9 cells with siRNA-mediated knockdown for Dbp or E2f8 promote and suppress tumor growth, respectively, in mouse tumor models. Importantly, DBP and E2F8 also exhibit opposing functions in regulating human TH9 differentiation in vitro. Thus, our data uncover a molecular mechanism of Smad3 linker region-mediated, opposing functions of DBP and E2F8 in Th9 differentiation.

Redox imbalance in COVID-19 pathophysiology.

BACKGROUND: The pathophysiologic significance of redox imbalance is unquestionable as numerous reports and topic reviews indicate alterations in redox parameters during corona virus disease 2019 (COVID-19). However, a more comprehensive understanding of redox-related parameters in the context of COVID-19-mediated inflammation and pathophysiology is required. METHODS: COVID-19 subjects (n = 64) and control subjects (n = 19) were enrolled, and blood was drawn within 72 h of diagnosis. Serum multiplex assays and peripheral blood mRNA sequencing was performed. Oxidant/free radical (electron paramagnetic resonance (EPR) spectroscopy, nitrite-nitrate assay) and antioxidant (ferrous reducing ability of serum assay and high-performance liquid chromatography) were performed. Multivariate analyses were performed to evaluate potential of indicated parameters to predict clinical outcome. RESULTS: Significantly greater levels of multiple inflammatory and vascular markers were quantified in the subjects admitted to the ICU compared to non-ICU subjects. Gene set enrichment analyses indicated significant enhancement of oxidant related pathways and biochemical assays confirmed a significant increase in free radical production and uric acid reduction in COVID-19 subjects. Multivariate analyses confirmed a positive association between serum levels of VCAM-1, ICAM-1 and a negative association between the abundance of one electron oxidants (detected by ascorbate radical formation) and mortality in COVID subjects while IL-17c and TSLP levels predicted need for intensive care in COVID-19 subjects. CONCLUSION: Herein we demonstrate a significant redox imbalance during COVID-19 infection affirming the potential for manipulation of oxidative stress pathways as a new therapeutic strategy COVID-19. However, further work is requisite for detailed identification of oxidants (O2•-, H2O2 and/or circulating transition metals such as Fe or Cu) contributing to this imbalance to avoid the repetition of failures using non-specific antioxidant supplementation.

Single B Cell Gene Co-Expression Networks Implicated in Prognosis, Proliferation, and Therapeutic Responses in Non-Small Cell Lung Cancer Bulk Tumors.

In NSCLC, there is a pressing need for immunotherapy predictive biomarkers. The processes underlying B-cell dysfunction, as well as their prognostic importance in NSCLC, are unknown. Tumor-specific B-cell gene co-expression networks were constructed by comparing the Boolean implication modeling of single-cell RNA sequencing of NSCLC tumor B cells and normal B cells. Proliferation genes were selected from the networks using in vitro CRISPR-Cas9/RNA interfering (RNAi) screening data in more than 92 human NSCLC epithelial cell lines. The prognostic and predictive evaluation was performed using public NSCLC transcriptome and proteome profiles. A B cell proliferation and prognostic gene co-expression network was present only in normal lung B cells and missing in NSCLC tumor B cells. A nine-gene signature was identified from this B cell network that provided accurate prognostic stratification using bulk NSCLC tumor transcriptome (n = 1313) and proteome profiles (n = 103). Multiple genes (HLA-DRA, HLA-DRB1, OAS1, and CD74) differentially expressed in NSCLC B cells, peripheral blood lymphocytes, and tumor T cells had concordant prognostic indications at the mRNA and protein expression levels. The selected genes were associated with drug sensitivity/resistance to 10 commonly used NSCLC therapeutic regimens. Lestaurtinib was discovered as a potential repositioning drug for treating NSCLC.

Preferential Antibody and Drug Conjugate Targeting of the ADAM10 Metalloprotease in Tumours.

ADAM10 is a transmembrane metalloprotease that sheds a variety of cell surface proteins, including receptors and ligands that regulate a range of developmental processes which re-emerge during tumour development. While ADAM10 is ubiquitously expressed, its activity is normally tightly regulated, but becomes deregulated in tumours. We previously reported the generation of a monoclonal antibody, 8C7, which preferentially recognises an active form of ADAM10 in human and mouse tumours. We now report our investigation of the mechanism of this specificity, and the preferential targeting of 8C7 to human tumour cell xenografts in mice. We also report the development of novel 8C7 antibody-drug conjugates that preferentially kill cells displaying the 8C7 epitope, and that can inhibit tumour growth in mice. This study provides the first demonstration that antibody-drug conjugates targeting an active conformer of ADAM10, a widely expressed transmembrane metalloprotease, enable tumour-selective targeting and inhibition.

A phase 1 safety and bioimaging trial of antibody DS-8895a against EphA2 in patients with advanced or metastatic EphA2 positive cancers.

Ephrin type-A 2 (EphA2) is a transmembrane receptor expressed in epithelial cancers. We report on a phase I dose escalation and biodistribution study of DS-8895a, an anti-EphA2 antibody, in patients with advanced EphA2 positive cancers. DS-8895a was administered at 1, 3, 10 or 20 mg/kg every 2 weeks to determine safety, pharmacokinetics and anti-tumor efficacy. All patients underwent 89Zr trace-labelled infusion of DS-8895a (89Zr-DS-8995a) positron emission tomography imaging to determine the biodistribution of DS-8895a, and correlate findings with EphA2 expression, receptor saturation and response. Nine patients were enrolled on study. Of patients enrolled, seven patients received at least one infusion of DS-8895a: four patients received 1 mg/kg dose (Cohort 1) and three patients received 3 mg/kg dose (Cohort 2). Median age was 67.0 years (range 52-81), majority male (71%), and median number of prior systemic therapies was three (range 0-8). The primary cancer diagnosis was colorectal cancer (two patients) and one patient each had gastric, head and neck, high-grade serous adenocarcinoma, lung, and pancreatic cancers. No dose-limiting toxicities or treatment-related adverse events reported. The best response for the patients in Cohort 1 was stable disease and in Cohort 2 was progressive disease. 89Zr-DS-8895a demonstrated no normal tissue uptake and specific low-grade uptake in most tumours. DS-8895a had limited therapeutic efficacy at doses evaluated and 89Zr-DS-8895a demonstrated low tumour uptake. The biodistribution data from this study were key in halting further development of DS-8895a, highlighting the importance of biodistribution studies in drug development. (Trial registration: ClinicalTrials.gov Identifier NCT02252211).

Inferencing Bulk Tumor and Single-Cell Multi-Omics Regulatory Networks for Discovery of Biomarkers and Therapeutic Targets.

There are insufficient accurate biomarkers and effective therapeutic targets in current cancer treatment. Multi-omics regulatory networks in patient bulk tumors and single cells can shed light on molecular disease mechanisms. Integration of multi-omics data with large-scale patient electronic medical records (EMRs) can lead to the discovery of biomarkers and therapeutic targets. In this review, multi-omics data harmonization methods were introduced, and common approaches to molecular network inference were summarized. Our Prediction Logic Boolean Implication Networks (PLBINs) have advantages over other methods in constructing genome-scale multi-omics networks in bulk tumors and single cells in terms of computational efficiency, scalability, and accuracy. Based on the constructed multi-modal regulatory networks, graph theory network centrality metrics can be used in the prioritization of candidates for discovering biomarkers and therapeutic targets. Our approach to integrating multi-omics profiles in a patient cohort with large-scale patient EMRs such as the SEER-Medicare cancer registry combined with extensive external validation can identify potential biomarkers applicable in large patient populations. These methodologies form a conceptually innovative framework to analyze various available information from research laboratories and healthcare systems, accelerating the discovery of biomarkers and therapeutic targets to ultimately improve cancer patient survival outcomes.