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Background Cynomolgus macaque ( Macaca fascicularis ) is an attractive animal model for the study of human disease and is extensively used in biomedical research. Cynomolgus macaques share behavioral, physiological, and genomic traits with humans and recapitulate human disease manifestations not observed in other animal species. To improve the use of the cynomolgus macaque model to investigate immune responses, we defined and characterized the T cell receptor (TCR) repertoire. Result We identified and analyzed the alpha (TRA), beta (TRB), gamma (TRG), and delta (TRD) TCR loci of the cynomolgus macaque. The expressed repertoire was determined using 22 unique lung samples from Mycobacterium tuberculosis infected cynomolgus macaques by single cell RNA sequencing. Expressed TCR alpha (TRAV) and beta (TRBV) variable region genes were enriched and identified using gene specific primers, which allowed their functional status to be determined. Analysis of the primers used for cynomolgus macaque TCR variable region gene enrichment showed they could also be used to amplify rhesus macaque ( M. mulatta ) variable region genes. Conclusion The genomic organization of the cynomolgus macaque has great similarity with the rhesus macaque and they shared > 90% sequence similarity with the human TCR repertoire. The identification of the TCR repertoire facilitates analysis of T cell immunity in cynomolgus macaques.

Cynomolgus macaque (Macaca fascicularis) is an attractive animal model for the study of human disease and is extensively used in biomedical research. Cynomolgus macaques share behavioral, physiological, and genomic traits with humans and recapitulate human disease manifestations not observed in other animal species. To improve the use of the cynomolgus macaque model to investigate immune responses, we defined and characterized the T cell receptor (TCR) repertoire. We identified and analyzed the alpha (TRA), beta (TRB), gamma (TRG), and delta (TRD) TCR loci of the cynomolgus macaque. The expressed repertoire was determined using 22 unique lung samples from Mycobacterium tuberculosis infected cynomolgus macaques by single cell RNA sequencing. Expressed TCR alpha (TRAV) and beta (TRBV) variable region genes were enriched and identified using gene specific primers, which allowed their functional status to be determined. Analysis of the primers used for cynomolgus macaque TCR variable region gene enrichment showed they could also be used to amplify rhesus macaque (M. mulatta) variable region genes. The genomic organization of the cynomolgus macaque has great similarity with the rhesus macaque and they shared > 90% sequence similarity with the human TCR repertoire. The identification of the TCR repertoire facilitates analysis of T cell immunity in cynomolgus macaques.

Background: Non-human primates (NHP) are desirable as animal models of human disease because they share behavioral, physiological, and genomic traits with people. Hence, NHP recapitulates manifestations of disease not observed in other animal species. The Macaca fascicularis (i.e., Cynomolgus macaque) is an NHP species extensively used for biomedical research, but the TCR repertoire has not been characterized yet. Result: We used the genomic sequences to design primers to identify the expressed TCR repertoire by single-cell RNAseq. The data analysis from 22 unique samples was used to assign a functional status to each TCR gene. We identified and analyzed the TRA/D, TRB, and TRG loci of the Cynomolgus macaque. Conclusion: The genomic organization of the Cynomolgus macaque has great similarity with Macaca mulatta (i.e., Rhesus macaque) and they shared >90% sequence similarity with the human TCR repertoire. These data will facilitate the analysis of T cell immunity in Cynomolgus macaques. Competing Interest Statement A.K.S. reports compensation for consulting and/or SAB membership from Merck, Honeycomb Biotechnologies, Cellarity, Repertoire Immune Medicines, Ochre Bio, Third Rock Ventures, Hovione, Relation Therapeutics, FL82, and Dahlia Biosciences.

Antigen-specific T cells play an essential role in immunoregulation and diseases such as cancer. Characterizing the T cell receptor (TCR) sequences that encode T cell specificity is critical for elucidating the antigenic determinants of immunological diseases and designing therapeutic remedies. However, methods of obtaining single-cell TCR sequencing data are labor and cost intensive, requiring cell sorting and full length single-cell RNA-sequencing (scRNA-seq). New high-throughput 3' cell-barcoding scRNA-seq methods can simplify and scale this process; however, they do not routinely capture TCR sequences during library preparation and sequencing. While 5' cell-barcoding scRNA-seq methods can be used to examine TCR repertoire at single-cell resolution, it requires specialized reagents which cannot be applied to samples previously processed using 3' cell-barcoding methods. Here, we outline a method for sequencing TCR\\(\\alpha\\) and TCR\\(\\beta\\) transcripts from samples already processed using 3' cell-barcoding scRNA-seq platforms, ensuring TCR recovery at a single-cell resolution. In short, a fraction of the 3' barcoded whole transcriptome amplification (WTA) product typically used to generate a massively parallel 3' scRNA-seq library is enriched for TCR transcripts using biotinylated probes, and further amplified using the same universal primer sequence from WTA. Primer extension using TCR V-region primers and targeted PCR amplification results in a 3' barcoded single-cell CDR3-enriched library that can be sequenced with custom sequencing primers. Coupled with 3' scRNA-seq of the same WTA, this method enables simultaneous analysis of single-cell transcriptomes and TCR sequences which can help interpret inherent heterogeneity among antigen-specific T cells and salient disease biology. This method can be adapted to enrich other transcripts of interest from 3' and 5' barcoded WTA libraries.

Introduction We hypothesized that serum neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios may predict pathologic complete response to neoadjuvant chemoradiotherapy in esophageal cancer patients. The ability to predict favorable treatment response to therapy may aid in determining optimal treatment regimens. Materials and Methods A retrospective review of a prospective esophageal disease registry was conducted. Neutrophil-to-lymphocyte ratio was defined as the pre-chemoradiotherapy serum neutrophil count divided by lymphocyte count. Platelet-to-lymphocyte ratio was similarly defined. Logistic regression was applied to analyze these ratios and their effect on pathologic complete response. A Cox proportional-hazards model was used to analyze survival. Results Sixty patients were included. Elevated neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio were both negative predictors of pathologic complete response (odds ratio: 0.62; 95% confidence interval: 0.37–0.89, P  = 0.037 and odds ratio: 0.91; 95% confidence interval: 0.82–0.98, P  = 0.028, respectively). Only platelet-to-lymphocyte ratio was predictive of decreased overall survival (hazard ratio: 1.05, 95% confidence interval: 0.94–1.16, P  = 0.40). Conclusion Elevated neutrophil and platelet-to-lymphocyte ratios were significant predictors of a poor treatment response to neoadjuvant therapy. Only elevated platelet-to-lymphocyte ratio was predictive of worse overall survival. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios may offer a simple serum test to assess the likelihood of a pathologic complete response after neoadjuvant therapy in esophageal cancer.

A reliable method to identify pathologic complete responders (pCR) or non-responders (NR) to neoadjuvant chemoradiation therapy (NAT) would dramatically improve therapy for esophageal cancer. The purpose of this study is to investigate if a distinct profile of prognostic molecular markers can predict pCR after neoadjuvant therapy. Expression of p53, Her-2/neu, Cox-2, Beta-catenin, E-cadherin, MMP-1, NFkB, and TGF-B was measured by immunohistochemistry in pre-treatment biopsy tissue and graded by an experienced pathologist. A pCR was defined as no evidence of malignancy on final pathology. Molecular profiles comparing responders to non-responders were analyzed using classification and regression tree analysis to investigate response to NAT and overall survival. Nineteen patients were pCRs and 34 were NRs. pCRs were more likely to be alive at follow-up than NRs ( p  < 0.01). Thirty-seven distinct profiles were identified. Expression of molecular markers was highly heterogeneous between patients and did not correlate with a response to NAT, survival ( p  = 0.47) or clinical stage ( p  = 0.39) when evaluated either as individual markers or in combination with other expression patterns. NAT dramatically impacts survival through a mechanism independent of known molecular markers of esophageal cancer, which are expressed in a highly heterogeneous fashion and do not predict response to NAT or survival.

Introduction The purpose of this study was to evaluate the effects of neoadjuvant therapy on lymph node harvest (LNH), lymph node ratio (LNR), and overall survival rates after esophagectomy. Methods A retrospective analysis of 111 patients who underwent esophagectomy for esophageal adenocarcinoma from 2001 to 2010 was performed. Patients were divided into two groups: neoadjuvant chemoradiotherapy prior to surgery (NEOSURG) versus surgery alone (SURG). Results There were 83 patients (75 %) in the NEOSURG group and 28 (25 %) in the SURG group with a mean age of 66 and 67 years, respectively. The median LNH in the NEOSURG group and SURG group was 16.0 and 15.5, respectively ( p  = 0.57). Within the NEOSURG group, the median LNH was 16 for complete responders, 14 for partial responders, 16 for nonresponders, and 18 in those who were pathologically upstaged ( p  = 0.434). The median LNR was 0, 0, 0.1, and 0.2, respectively ( p  < 0.001). Complete response after neoadjuvant therapy demonstrated a trend toward improved survival ( p  = 0.056). Conclusion The LNH was not significantly influenced by neoadjuvant treatment or pathologic response. The LNR was inversely related to pathologic response after neoadjuvant therapy. Complete pathologic response to neoadjuvant therapy trends to improve survival rates.