Successful Treatment of Severe COVID-19 Pneumonia With Clazakizumab in a Heart Transplant Recipient: A Case Report

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is characterized by an overwhelming cytokine response. Various treatment strategies have been attempted.

METHODS AND RESULTS

A 61-year-old man with heart transplantation in 2017 presented with fever, cough, and dyspnea, and was confirmed positive for coronavirus disease 2019 (COVID-19). Laboratory tests showed significant elevations in C-reactive protein and interleukin-6 (IL-6). Echocardiogram showed left ventricular ejection fraction 58% (with ejection fraction 57% 6 months prior). Given the lack of clear management guidelines, the patient was initially managed symptomatically. However, the patient subsequently had a rapid respiratory deterioration with worsening inflammatory markers on day 5 of admission. Tocilizumab (anti-IL-6R) was in low supply in the hospital. The patient was offered clazakizumab (anti-IL-6) for compassionate use. Patient received 25 mg intravenously × 1 dose. Within 24 hours, he showed significant improvement in symptoms, oxygen requirements, radiological findings, and inflammatory markers. There was a transient leukopenia that improved in 4 days. He was discharged home on day 11, with negative nasopharyngeal SARS-CoV-2 PCR as an outpatient on day 35, development of positive serum COVID-19 IgG antibody, and he continued to do well on day 60, with no heart-related symptoms.

CONCLUSION

Clazakizumab is a monoclonal antibody against human IL-6, which may be helpful in inhibiting the cytokine response to SARS-CoV-2 in COVID-19. Although not yet FDA approved, it is being investigated for treatment of renal antibody-mediated rejection. Clinical trials of clazakizumab for treatment of COVID-19 are underway worldwide.

Neoadjuvant Chemotherapy Increases Cytotoxic T Cell, Tissue Resident Memory T Cell, and B Cell Infiltration in Resectable NSCLC

INTRODUCTION

The combination of programmed cell death protein-1 or programmed death-ligand 1 immune checkpoint blockade and chemotherapy has revolutionized the treatment of advanced NSCLC, but the mechanisms underlying this synergy remain incompletely understood. In this study, we explored the relationships between neoadjuvant chemotherapy and the immune microenvironment (IME) of resectable NSCLC to identify novel mechanisms by which chemotherapy may enhance the effect of immune checkpoint blockade.

METHODS

Genomic, transcriptomic, and immune profiling data of 511 patients treated with neoadjuvant chemotherapy followed by surgery (NCT) versus upfront surgery (US) were compared with determined differential characteristics of the IMEs derived from whole-exome sequencing (NCT = 18; US = 73), RNA microarray (NCT = 45; US = 202), flow cytometry (NCT = 17; US = 39), multiplex immunofluorescence (NCT = 10; US = 72), T-cell receptor sequencing (NCT = 16 and US = 63), and circulating cytokines (NCT = 18; US = 73).

RESULTS

NCT was associated with increased infiltration of cytotoxic CD8⁺ T cells and CD20⁺ B cells. Moreover, NCT was associated with increases in CD8⁺CD103⁺ and CD4⁺CD103⁺PD-1⁺TIM3^- tissue resident memory T cells. Gene expression profiling supported memory function of CD8⁺ and CD4⁺ T cells. However, NCT did not affect T-cell receptor clonality, richness, or tumor mutational burden. Finally, NCT was associated with decreased plasma BDNF (TrkB) at baseline and week 4 after surgery.

CONCLUSIONS

Our study supports that, in the context of resectable NSCLC, neoadjuvant chemotherapy promotes antitumor immunity through T and B cell recruitment in the IME and through a phenotypic change toward cytotoxic and memory CD8⁺ and CD4⁺ memory helper T cells.

A Standardized Multimodal Analgesia Protocol Reduces Perioperative Opioid Use in Minimally Invasive Colorectal Surgery

BACKGROUND

Multimodal analgesia protocols are becoming a common part of enhanced recovery pathways after colorectal surgery. However, few protocols include a robust intraoperative component in addition to pre-operative and post-operative analgesics.

METHOD

A prospective cohort study was performed in an urban teaching hospital in patients undergoing minimally invasive colorectal surgery before and after implementation of a multimodal analgesia protocol consisting of pre-operative (gabapentin, acetaminophen, celecoxib), intraoperative (lidocaine and magnesium infusions, ketorolac, transversus abdominis plane block), and post-operative (gabapentin, acetaminophen, celecoxib) opioid-sparing elements. The main outcome measure was use of morphine equivalents in the first 24-h post-operative period.

RESULTS

The study cohort (n = 71) included 41 patients before and 30 patients after implementation of a multimodal analgesia protocol. Mean age of the entire study cohort was 47 ± 19.7 years and 46% were male. Patients undergoing surgery post-multimodal analgesia vs. pre-multimodal analgesia had significantly lower use of IV morphine equivalents in first 24-h post-operative period (5.8 ± 6.4 mg vs. 22.8 ± 21.3 mg; p = 0.005) and first 48-h post-operative period (7.6 ± 9.4 mg vs. 42 ± 52.9 mg; p = 0.0008). This reduction in IV morphine equivalent use post-multimodal analgesia was coupled with improved pain scores in the post-operative period. Post-operative hospital length of stay, post-operative ileus, and overall complications were not significantly different between groups.

CONCLUSIONS

Multimodal analgesia incorporating pre-operative, intraoperative, and post-operative opioid-sparing agents is an effective method for reducing perioperative opioid utilization and pain after minimally invasive colorectal surgery.

(Un)intended consequences? The impact of the 2017 tax cuts and jobs act on shareholder wealth

We study the stock market reactions to the Tax Cuts and Jobs Act (TCJA), the most significant structural U.S. tax reform in over 30 years. In line with the stated intent of TCJA proponents, we find that the Act benefited highly taxed firms. However, the Act hindered firms with international operations as well as firms with high interest expense and tax losses. Counter to claims that the TCJA would quickly spur economic growth, we find that financially constrained and high growth opportunity firms did not benefit. Rather, market participants anticipate that most of the TCJA's benefits will be passed on to shareholders via higher corporate payouts. We confirm these market expectations by documenting that firms did increase payouts via repurchases after the TCJA, but did not increase their corporate investments.

Abstract 1496: Paired, single-cell profiling of circulating tumor cell-derived xenograft models of small cell lung cancer reveals intratumoral heterogeneity and emergence of new cell clusters following treatment relapse

Small cell lung cancer (SCLC), the most aggressive form of lung cancer, is notable for early dissemination and impressive, yet transient, responses to frontline chemotherapy that are rapidly undone by refractory relapses. To gain a better understanding of resistance mechanisms, we generated circulating tumor cell-derived xenograft (CDX) models from liquid biopsies of SCLC patients and treated them with chemotherapy or targeted agents. As expected, CDXs demonstrate similar chemotherapy response to the patient from whom they were derived. We have previously established that baseline chemosensitive CDXs are molecularly homogeneous at the single cell level, while chemoresistant CDXs exhibit increased intratumoral heterogeneity (ITH) with distinct variations in gene expression between cancer cell populations. We hypothesize that paired analyses of chemosensitive CDXs will demonstrate increased ITH after developing acquired resistance and are likely to offer more specific insights into resistance mechanisms than prior work with unrelated CDX models. Platinum-sensitive CDXs were treated with cisplatin or DNA damage response targeted therapies (PARP inhibitor or CHK inhibitor) continuously until tumor progression was observed. To identify transcriptional changes associated with onset of resistance, single-cell RNAseq analysis was performed on vehicle-treated and relapsed CDX tumors. We found globally increased ITH including heterogeneous expression of therapeutic targets and potential resistance pathways, such as EMT, between cellular subpopulations following treatment-resistance. Relapse was consistently associated with increased ITH score (P<0.001) and cell cluster number. To determine whether transcriptional diversity in either therapeutic targets (ex., MYC, DLL3, TOP2A, PARP1, CHEK1, EZH2, etc.) or EMT genes (ex., ZEB1, ZEB2, TWIST1, VIM, AXL) was detectable between the paired tumors after onset of resistance, we compared transcriptional differences between clusters present in vehicle-treated versus cisplatin or targeted therapy-treated tumors. We discovered the emergence of new cell clusters in relapsed tumors in all CDX models (4 CDXs, 3 distinct treatments), including clusters expressing EMT or NOTCH signaling genes. These data suggest that, in response to treatment, SCLC develops increasing transcriptional ITH marked by concurrent, diverse resistant cell clusters. Clinically, these data underscore the importance of maximizing and maintaining the initial response in platinum-sensitive SCLC tumors and highlight the intrinsic transcriptional fluidity underlying SCLC's profound treatment resistance following initial therapy.

Citation Format: C. Allison Stewart, Carl M. Gay, Yuanxin Xi, Santhosh Sivajothi, Junya Fujimoto, Patrice M. Hartsfield, Hai Tran, Stephen G. Swisher, Jack A. Roth, Jianjun Zhang, Bonnie Glisson, John V. Heymach, Ignacio Wistuba, Paul Robson, Jing Wang, Lauren A. Byers. Paired, single-cell profiling of circulating tumor cell-derived xenograft models of small cell lung cancer reveals intratumoral heterogeneity and emergence of new cell clusters following treatment relapse [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1496.

Stochastic ordering of complexoform protein assembly by genetic circuits

Top-down proteomics has enabled the elucidation of heterogeneous protein complexes with different cofactors, post-translational modifications, and protein membership. This heterogeneity is believed to play a previously unknown role in cellular processes. The different molecular forms of a protein complex have come to be called “complex isoform” or “complexoform”. Despite the elucidation of the complexoform, it remains unclear how and whether cellular circuits control the distribution of a complexoform. To help address this issue, we first simulate a generic three-protein complexoform to reveal the control of its distribution by the timing of gene transcription, mRNA translation, and protein transport. Overall, we ran 265 computational experiments: each averaged over 1,000 stochastic simulations. Based on the experiments, we show that genes arranged in a single operon, a cascade, or as two operons all give rise to the different protein composition of complexoform because of timing differences in protein-synthesis order. We also show that changes in the kinetics of expression, protein transport, or protein binding dramatically alter the distribution of the complexoform. Furthermore, both stochastic and transient kinetics control the assembly of the complexoform when the expression and assembly occur concurrently. We test our model against the biological cellulosome system. With biologically relevant rates, we find that the genetic circuitry controls the average final complexoform assembly and the variation in the assembly structure. Our results highlight the importance of both the genetic circuit architecture and kinetics in determining the distribution of a complexoform. Our work has a broad impact on our understanding of non-equilibrium processes in both living and synthetic biological systems.

Multiple protein subunits can come together to form protein complexes that play critical functional roles in a cell. Recent advancement in measurement technologies has revealed tremendous variation in the members of protein complexes. The recent results motivate further research into the importance and the underlying mechanisms of the variation. Here, we study the arrangement of genes as a key factor that modulates the variation of protein complexes. We run computer simulations to investigate how various reaction parameters control the variation of a protein complex. Finally, we extend our framework to study the variation of an enzymatic complex that digests cellulose. Our work has a broad impact on the understanding of protein-complex assembly and set up the new research direction about the variation of protein complexes.

Development of feed composition tables using a statistical screening procedure

Millions of feed composition records generated annually by testing laboratories are valuable assets that can be used to benefit the animal nutrition community. However, it is challenging to manage, handle, and process feed composition data that originate from multiple sources, lack standardized feed names, and contain outliers. Efficient methods that consolidate and screen such data are needed to develop feed composition databases with accurate means and standard deviations (SD). Considering the interest of the animal science community in data management and the importance of feed composition tables for the animal industry, the objective was to develop a set of procedures to construct accurate feed composition tables from large data sets. A published statistical procedure, designed to screen feed composition data, was employed, modified, and programmed to operate using Python and SAS. The 2.76 million data received from 4 commercial feed testing laboratories were used to develop procedures and to construct tables summarizing feed composition. Briefly, feed names and nutrients across laboratories were standardized, and erroneous and duplicated records were removed. Histogram, univariate, and principal component analyses were used to identify and remove outliers having key nutrients outside of the mean ± 3.5 SD. Clustering procedures identified subgroups of feeds within a large data set. Aside from the clustering step that was programmed in Python to automatically execute in SAS, all steps were programmed and automatically conducted using Python followed by a manual evaluation of the resulting mean Pearson correlation matrices of clusters. The input data set contained 42, 94, 162, and 270 feeds from 4 laboratories and comprised 25 to 30 nutrients. The final database included 174 feeds and 1.48 million records. The developed procedures effectively classified by-products (e.g., distillers grains and solubles as low or high fat), forages (e.g., legume or grass-legume mixture by maturity), and oilseeds versus meal (e.g., soybeans as whole raw seeds vs. soybean meal expellers or solvent extracted) into distinct sub-populations. Results from these analyses suggest that the procedure can provide a robust tool to construct and update large feed data sets. This approach can also be used by commercial laboratories, feed manufacturers, animal producers, and other professionals to process feed composition data sets and update feed libraries.

Single-cell analyses reveal increased intratumoral heterogeneity after the onset of therapy resistance in small-cell lung cancer

The natural history of small cell lung cancer (SCLC) includes rapid evolution from chemosensitivity to chemoresistance, although mechanisms underlying this evolution remain obscure due to scarcity of post-relapse tissue samples. We generated circulating tumor cell (CTC)-derived xenografts (CDXs) from SCLC patients to study intratumoral heterogeneity (ITH) via single-cell RNAseq of chemo-sensitive and -resistant CDXs and patient CTCs. We found globally increased ITH including heterogeneous expression of therapeutic targets and potential resistance pathways, such as EMT, between cellular subpopulations following treatment-resistance. Similarly, serial profiling of patient CTCs directly from blood confirmed increased ITH post-relapse. These data suggest that treatment-resistance in SCLC is characterized by coexisting subpopulations of cells with heterogeneous gene expression leading to multiple, concurrent resistance mechanisms. These findings emphasize the need for clinical efforts to focus on rational combination therapies for treatment-naïve SCLC tumors to maximize initial responses and counteract the emergence of ITH and diverse resistance mechanisms.

Combining Immune Checkpoint Blockade and Tumor-Specific Vaccine for Patients With Incurable Human Papillomavirus 16-Related Cancer: A Phase 2 Clinical Trial

Importance

In recurrent human papilloma virus (HPV)-driven cancer, immune checkpoint blockade with anti-programmed cell death 1 (PD-1) antibodies produces tumor regression in only a minority of patients. Therapeutic HPV vaccines have produced strong immune responses to HPV-16, but vaccination alone has been ineffective for invasive cancer.

Objective

To determine whether the efficacy of nivolumab, an anti-PD-1 immune checkpoint antibody, is amplified through treatment with ISA 101, a synthetic long-peptide HPV-16 vaccine inducing HPV-specific T cells, in patients with incurable HPV-16-positive cancer.

Design, Setting, and Participants

In this single-arm, single-center phase 2 clinical trial, 24 patients with incurable HPV-16-positive cancer were enrolled from December 23, 2015, to December 12, 2016. Duration of follow-up for censored patients was 12.2 months through August 31, 2017.

Interventions

The vaccine ISA101, 100 μg/peptide, was given subcutaneously on days 1, 22, and 50. Nivolumab, 3 mg/kg, was given intravenously every 2 weeks beginning day 8 for up to 1 year.

Main Outcomes and Measures

Assessment of efficacy reflected in the overall response rate (per Response Evaluation Criteria in Solid Tumors, version 1.1).

Results

Of the 24 patients (4 women and 20 men; 22 with oropharyngeal cancer; median age, 60 years [range, 36-73 years]), the overall response rate was 33% (8 patients; 90% CI, 19%-50%). Median duration of response was 10.3 months (95% CI, 10.3 months to inestimable). Five of 8 patients remain in response. Median progression-free survival was 2.7 months (95% CI, 2.5-9.4 months). Median overall survival was 17.5 months (95% CI, 17.5 months to inestimable). Grades 3 to 4 toxicity occurred in 2 patients (asymptomatic grade 3 transaminase level elevation in 1 patient and grade 4 lipase elevation in 1 patient), requiring discontinuation of nivolumab therapy.

Conclusions and Relevance

The overall response rate of 33% and median overall survival of 17.5 months is promising compared with PD-1 inhibition alone in similar patients. A randomized clinical trial to confirm the contribution of HPV-16 vaccination to tumoricidal effects of PD-1 inhibition is warranted for further study.

Trial Registration

ClinicalTrials.gov identifier: NCT02426892.

Predictions of ruminal outflow of essential amino acids in dairy cattle

The objective of this work was to update and evaluate predictions of essential AA (EAA) outflows from the rumen. The model was constructed based on previously derived equations for rumen-undegradable (RUP), microbial (MiCP), and endogenous (EndCP) protein outflows from the rumen, and revised estimates of ingredient composition and EAA composition of the protein fractions. Corrections were adopted to account for incomplete recovery of EAA during 24-h acid hydrolysis. The predicted ruminal protein and EAA outflows were evaluated against a data set of observed values from the literature. Initial evaluations indicated a minor mean bias for non-ammonia, non-microbial nitrogen flow ([RUP + EndCP]/6.25) of 16 g of N per day. Root mean squared errors (RMSE) of EAA predictions ranged from 26.8 to 40.6% of observed mean values. Concordance correlation coefficients (CCC) of EAA predictions ranged from 0.34 to 0.55. Except for Leu, all ruminal EAA outflows were overpredicted by 3.0 to 32 g/d. In addition, small but significant slope biases were present for Arg [2.2% mean squared error (MSE)] and Lys (3.2% MSE). The overpredictions may suggest that the mean recovery of AA from acid hydrolysis across laboratories was less than estimates encompassed in the recovery factors. To test this hypothesis, several regression approaches were undertaken to identify potential causes of the bias. These included regressions of (1) residual errors for predicted EAA flows on each of the 3 protein-driven EA flows, (2) observed EAA flows on each protein-driven EAA flow, including an intercept, (3) observed EAA flows on the protein-driven EAA flows, excluding an intercept term, and (4) observed EAA flows on RUP and MiCP. However, these equations were deemed unsatisfactory for bias adjustment, as they generated biologically unfeasible predictions for some entities. Future work should focus on identifying the cause of the observed prediction bias.