Background Learning patient outcomes is recognized as crucial for ongoing refinement of clinical decision-making, but is often difficult in fragmented care with frequent handoffs. Data on resident habits of seeking outcome feedback after handoffs are lacking. Methods We performed a mixed-methods study including (1) an analysis of chart re-access rates after handoffs performed using access logs of the electronic health record (EHR); and (2) a web-based survey sent to internal medicine (IM) and emergency medicine (EM) residents about their habits of and barriers to learning the outcomes of patients after they have handed them off to other teams. Results Residents on ward rotations were often able to re-access charts of patients after handoffs, but those on EM or night admitting rotations did so <5% of the time. Among residents surveyed, only a minority stated that they frequently find out the outcomes of patients they have handed off, although learning outcomes was important to both their education and job satisfaction. Most were not satisfied with current systems of learning outcomes of patients after handoffs, citing too little time and lack of reliable patient tracking systems as the main barriers. Conclusions Despite perceived importance of learning outcomes after handoffs, residents cite difficulty with obtaining such information. Systematically providing feedback on patient outcomes would meet a recognized need among physicians in training.

The T and B cell repertoire make up the adaptive immune system and is mainly generated through somatic V(D)J gene recombination. Thus, the VJ gene usage may be a potential prognostic or predictive biomarker. However, analysis of the adaptive immune system is challenging due to the heterogeneity of the clonotypes that make up the repertoire. To address the heterogeneity of the T and B cell repertoire, we proposed a novel ensemble feature selection approach and customized statistical learning algorithm focusing on the VJ gene usage. We applied the proposed approach to T cell receptor sequences from recovered COVID-19 patients and healthy donors, as well as a group of lung cancer patients who received immunotherapy. Our approach identified distinct VJ genes used in the COVID-19 recovered patients comparing to the healthy donors and the VJ genes associated with the clinical response in the lung cancer patients. Simulation studies show that the ensemble feature selection approach outperformed other state-of-the-art feature selection methods based on both efficiency and accuracy. It consistently yielded higher stability and sensitivity with lower false discovery rates. When integrated with different classification methods, the ensemble feature selection approach had the best prediction accuracy. In conclusion, the proposed novel approach and the integration procedure is an effective feature selection technique to aid in correctly classifying different subtypes to better understand the signatures in the adaptive immune response associated with disease or the treatment in order to improve treatment strategies.

T cells represent a crucial component of the adaptive immune system and mediate anti-tumoral immunity as well as protection against infections, including respiratory viruses such as SARS-CoV-2. Next-generation sequencing of the T-cell receptors (TCRs) can be used to profile the T-cell repertoire. We developed a customized pipeline for Network Analysis of Immune Repertoire (NAIR) with advanced statistical methods to characterize and investigate changes in the landscape of TCR sequences. We first performed network analysis on the TCR sequence data based on sequence similarity. We then quantified the repertoire network by network properties and correlated it with clinical outcomes of interest. In addition, we identified (1) disease-specific/associated clusters and (2) shared clusters across samples based on our customized search algorithms and assessed their relationship with clinical outcomes such as recovery from COVID-19 infection. Furthermore, to identify disease-specific TCRs, we introduced a new metric that incorporates the clonal generation probability and the clonal abundance by using the Bayes factor to filter out the false positives. TCR-seq data from COVID-19 subjects and healthy donors were used to illustrate that the proposed approach to analyzing the network architecture of the immune repertoire can reveal potential disease-specific TCRs responsible for the immune response to infection.

Immune checkpoint inhibitors (ICI) are designed to activate exhausted tumor-reactive T cells thereby leading to tumor regression. Durvalumab, an ICI that binds to the programmed death ligand-1 (PD-L1) molecule, is approved as a consolidation therapy for treatment of patients with stage III, unresectable, non-small cell lung cancer (NSCLC). Immunophenotypic analysis of circulating immune cells revealed increases in circulating proliferating CD4 + and CD8 + T cells earlier after durvalumab treatment. To examine durvalumab's mechanism of action and identify potential predictive biomarkers, we assessed the circulating T cells phenotypes and TCR genes of 71 NSCLC patients receiving durvalumab enrolled in a Phase I trial (NCT01693562, September 14, 2012). Next-generation sequencing of TCR repertoire was performed on these NSCLC patients' peripheral blood samples at baseline and day 15. Though patients' TCR repertoire diversity showed mixed responses to the treatment, patients exhibiting increased diversity on day 15 attained significantly longer overall survival (OS) (median OS was not reached vs 17.2 months for those with decreased diversity, p = 0.015). We applied network analysis to assess convergent T cell clonotypes indicative of an antigen-driven immune response. Patients with larger TCR clusters had improved OS (median OS was not reached vs 13.1 months for patients with smaller TCR clusters, p = 0.013). Early TCR repertoire diversification after durvalumab therapy for NSCLC may be predictive of increased survival and provides a mechanistic basis for durvalumab pharmacodynamic activity.

Sipuleucel-T is an autologous cellular immunotherapy, administered as three infusions, for metastatic castration-resistant prostate cancer (mCRPC). Sipuleucel-T induces T- and B-cell responses to prostatic acid phosphatase (PAP), correlating to improved survival. The long-term impact of sipuleucel-T on tumor antigen-specific immunologic memory remains unknown, in particular, B-cell responses, as measured by antigen-specific antibody responses and B-cell receptor (BCR) sequences. To evaluate whether sipuleucel-T could induce long-term immunologic memory, we examined circulating B-cell responses before and after sipuleucel-T treatment in two groups of patients with mCRPC: those who had previously received sipuleucel-T (treated; median, 8.9 years since the previous treatment) versus those who had not (naïve). Before re-treatment, previously treated patients exhibited persistent antibody responses as well as more focused and convergent BCR repertoires with distinct V(D)J gene usage compared with naïve patients. After re-treatment, previously treated patients maintained high-frequency clones and developed more convergent BCRs at earlier time points unlike naïve patients. With the first sipuleucel-T infusion specifically, previously treated patients had less shuffling within the 100 most abundant baseline clones. In contrast, naïve patients exhibited great BCR turnover with a continued influx of new B-cell clones. Social network analysis showed that previously treated patients had more highly organized B-cell repertoires, consistent with greater clonal maturation. Higher treatment-induced BCR clonality correlated with longer survival for naïve patients. These results demonstrated the capacity of sipuleucel-T to induce long-term immune memory and lasting changes to the B-cell repertoire.

Denosumab is a fully human mAb that binds receptor activator of NFκB ligand (RANKL). It is routinely administered to patients with cancer to reduce the incidence of new bone metastasis. RANK-RANKL interactions regulate bone turnover by controlling osteoclast recruitment, development, and activity. However, these interactions also can regulate immune cells including dendritic cells and medullary thymic epithelial cells. Inhibition of the latter results in reduced thymic negative selection of T cells and could enhance the generation of tumor-specific T cells. We examined whether administering denosumab could modify modulate circulating immune cells in patients with cancer. Blood was collected from 23 patients with prostate cancer and 3 patients with renal cell carcinoma, all of whom had advanced disease and were receiving denosumab, prior to and during denosumab treatment. Using high-dimensional mass cytometry, we found that denosumab treatment by itself induced modest effects on circulating immune cell frequency and activation. We also found minimal changes in the circulating T-cell repertoire and the frequency of new thymic emigrants with denosumab treatment. However, when we stratified patients by whether they were receiving chemotherapy and/or steroids, patients receiving these concomitant treatments showed significantly greater immune modulation, including an increase in the frequency of natural killer cells early and classical monocytes later. We also saw broad induction of CTLA-4 and TIM3 expression in circulating lymphocytes and some monocyte populations. These findings suggest that denosumab treatment by itself has modest immunomodulatory effects, but when combined with conventional cancer treatments, can lead to the induction of immunologic checkpoints. See related Spotlight by Nasrollahi and Davar, p. 383.

Sotigalimab is an agonistic anti-CD40 monoclonal antibody that can modulate anti-tumor immune responses. In a phase II clinical trial of sotigalimab combined with neoadjuvant chemoradiation (CRT) in locally advanced esophageal/gastroesophageal junction (E/GEJ) cancer with the primary outcome of efficacy as measured by pathologic complete response (pCR) rate, the combination induced pCR in 38% of treated patients. We investigated the mechanism of action of sotigalimab in samples obtained from this clinical trial. Tumor biopsies and peripheral blood samples were collected at baseline, following an initial dose of sotigalimab, and at the time of surgery after CRT completion from six patients. High dimensional single cell techniques were used, including combined single cell RNA sequencing and proteomics (CITEseq) and multiplexed ion beam imaging (MIBI), to analyze immune responses. Sotigalimab dramatically re-modeled the immune compartment in the periphery and within the tumor microenvironment (TME), increasing expression of molecules related to antigen processing and presentation and altering metabolic pathways in myeloid cells. Concomitant with these changes in myeloid cells, sotigalimab treatment primed new T cell clonotypes and increased the density and activation of T cells with enhanced cytotoxic function. Sotigalimab treatment also induced a decrease in the frequency of Tregs in the TME. These findings indicate that a single dose of sotigalimab leads to enhanced antigen presentation that can activate T cells and induce new T cell clones. This restructuring of the TME provides elements which are critical to the development of effective antitumor immune responses and improved clinical outcomes.

Kawasaki disease (KD) is the most common acquired pediatric heart disease. We analyzed Whole Genome Sequences (WGS) from a 6-member African American family in which KD affected two of four children. We sought rare, potentially causative genotypes by sequentially applying the following WGS filters: sequence quality scores, inheritance model (recessive homozygous and compound heterozygous), predicted deleteriousness, allele frequency, genes in KD-associated pathways or with significant associations in published KD genome-wide association studies (GWAS), and with differential expression in KD blood transcriptomes. Biologically plausible genotypes were identified in twelve variants in six genes in the two affected children. The affected siblings were compound heterozygous for the rare variants p.Leu194Pro and p.Arg247Lys in Toll-like receptor 6 (TLR6), which affect TLR6 signaling. The affected children were also homozygous for three common, linked (r2 = 1) intronic single nucleotide variants (SNVs) in TLR6 (rs56245262, rs56083757 and rs7669329), that have previously shown association with KD in cohorts of European descent. Using transcriptome data from pre-treatment whole blood of KD subjects (n = 146), expression quantitative trait loci (eQTL) analyses were performed. Subjects homozygous for the intronic risk allele (A allele of TLR6 rs56245262) had differential expression of Interleukin-6 (IL-6) as a function of genotype (p = 0.0007) and a higher erythrocyte sedimentation rate at diagnosis. TLR6 plays an important role in pathogen-associated molecular pattern recognition, and sequence variations may affect binding affinities that in turn influence KD susceptibility. This integrative genomic approach illustrates how the analysis of WGS in multiplex families with a complex genetic disease allows examination of both the common disease-common variant and common disease-rare variant hypotheses.