T-cell exhaustion: A potential target biomarker of the tumour microenvironment affecting esophageal adenocarcinoma

BACKGROUND

Esophageal adenocarcinoma (EAC) is one of the most common malignant tumors, and the number of patients is increasing year by year. T-cell exhaustion (TEX) is an important risk factor for tumor immunosuppression and invasion, but its underlying mechanism in the pathogenesis of EAC is not clear.

METHODS

Unsupervised clustering was performed to screen relevant genes based on Gene Set Variation Analysis (GSVA) scores of the three pathways of the HALLMARK gene set IL2\IFNG\TNFA. Multiple enrichment analyses and data combinations were used to depict the relationship between TEX-related risk models and CIBERSORTX immune infiltrating cells. In addition, to explore the impact of TEX on EAC therapeutic resistance, we assessed the impact of TEX risk models on the therapeutic sensitivity of various novel drugs using single cell sequencing and searched for their potential therapeutic targets and cellular communication.

RESULTS

Four risk Clusters of EAC patients were identified by unsupervised clustering and searched for potential TEX-related genes. And based on this, LASSO regression and decision trees were used to construct risk prognostic models containing a total of 3 TEX-associated genes in EAC. The results showed that TEX risk scores were significantly associated with survival prognosis of EAC patients in both the TCGA dataset and the independent validation set of GEO. Immune infiltration and cell communication analyses identified Mast cell resting as a protective factor in TEX, and pathway enrichment analyses showed that the TEX risk model was highly associated with multiple chemokines as well as inflammation-associated pathways. In addition, higher TEX risk scores were associated with a weak responsiveness to immunotherapy.

CONCLUSION

We describe the immune infiltration, prognostic significance and potential possible mechanisms of TEX in the EAC patient population. This is a novel attempt to promote the development of novel therapeutic modalities and immunological target construction for esophageal adenocarcinoma. It's expected to make a potential contribution to advancing the exploration of immunological mechanisms and the opening of targeted drugs in EAC.

Evaluation of the Efficacy and Complications of Uterine Artery Embolization in Comparison with Laparotomy-Myomectomy in the Treatment of Uterine Myomas: A Randomized Clinical Trial

Background: Due to the high prevalence of uterine fibroids or leiomyomas in women of reproductive age and the many treatment options for myomas, finding the best treatment is a challenge for surgeons. Therefore, this study aimed at evaluating the efficacy and safety of 2 treatment options surgical interventions and uterine artery embolization (UAE) in patients with uterine myoma.

Methods: The present study was a single-blind randomized clinical trial. The study population included all women with uterine myoma. Hence, 80 patients were divided into 2 groups of 40. The first group underwent laparotomy-myomectomy and the second underwent UAE. These patients were evaluated for clinical symptoms, menstrual disorders, estimated blood loss per menstrual cycle, and pain and complication on the 10th day, and at 2, 6, and 12 months after the intervention. The data were analyzed with SPSS software (Version 25) using an independent samples t test, a repeated measure analysis, and a chi-square test.

Results: Ten days, 2, 6, and 12 months after the intervention, there was no significant difference between the 2 approaches in terms of their decreasing effects on per menstrual cycle blood loss (p > 0.05), respectively. After 10 days and 2 months, the pain intensity in the embolization group was higher than laparotomy group (p = 0.045, 0.060), respectively. The pain intensity was also not significantly different between the 2 groups after 6 months and 1 year (p > 0.05), respectively. Also, the frequency of fever was higher in the embolization group (p = 0.745). However, the documented post-procedural complications indicated that hemoglobin level declined post-operation (p > 0.050).

Conclusion: The results showed no significant difference between the 2 groups in terms of post-procedural mensuration blood loss or pain intensity and the incidence of menstrual disorders within 1 year. It seems that there is no significant difference between the 2 groups and it may be possible to use the UAE depending on the patient's condition.

Appreciating the Nuance of Daily Symptom Variation to Individualize Patient Care

Introduction:

Improving symptoms for patients with chronic illness is difficult due to poor recall and imprecise assessments of therapeutic response to inform treatment decisions. Daily variation in symptoms may obscure subtle improvement or lead to erroneous associations between symptom changes and alteration in medication or dietary regimens. This may lead to mistaken impressions of treatment efficacy (or inefficacy). Mobile health technologies that collect daily patient reported outcome (PRO) data have the potential to improve care by providing more detailed information for clinical decision-making in practice and may facilitate conducting single subject (n-of-1) trials.

Methods:

Interrupted time series to prototype mobile health enabled data collection for three patients. We recruited pediatric patients with established inflammatory bowel disease who had persistent symptoms. Based on their self-identified most troubling symptoms, patients were sent customized, daily-automated text messages to assess the extent of their symptoms. Standardized, PRO Measurement Information System (PROMIS) surveys were deployed weekly. Individual statistical process control charts were used to assess variation. Patients met with physicians regularly to interpret their data jointly.

Results:

We report the experience of 3 patients with inflammatory bowel disease, each with different symptoms. Daily symptom monitoring uncovered important patterns, some of which even patients were unaware before reviewing their symptom data. Important associations were found between symptom variation and changes in medications and diet. PROMIS survey results assessed longitudinally accurately reflected changes in patient symptoms.

Conclusions:

We demonstrated how PROs can be implemented in practice. Monitoring and analyzing daily symptom data, using both customized and standard PROs, has the potential to detect meaningful variation in symptom patterns, which can inform clinical decision-making or can facilitate conducting formal n-of-1 trials to further improve outcomes.

"The molecule's the thing:" the promise of molecular modeling and dynamic simulations in aiding the prioritization and interpretation of genomic testing results

Clinical genomics is now a reality and lies at the heart of individualized medicine efforts. The success of these approaches is evidenced by the increasing volume of publications that report causal links between genomic variants and disease. In spite of early success, clinical genomics currently faces significant challenges in establishing the relevance of the majority of variants identified by next generation sequencing tests. Indeed, the majority of mutations identified are harbored by proteins whose functions remain elusive. Herein we describe the current scenario in genomic testing and in particular the burden of variants of uncertain significance (VUSs). We highlight a role for molecular modeling and molecular dynamic simulations as tools that can significantly increase the yield of information to aid in the evaluation of pathogenicity. Though the application of these methodologies to the interpretation of variants identified by genomic testing is not yet widespread, we predict that an increase in their use will significantly benefit the mission of clinical genomics for individualized medicine.

"The molecule's the thing:" the promise of molecular modeling and dynamic simulations in aiding the prioritization and interpretation of genomic testing results

Clinical genomics is now a reality and lies at the heart of individualized medicine efforts. The success of these approaches is evidenced by the increasing volume of publications that report causal links between genomic variants and disease. In spite of early success, clinical genomics currently faces significant challenges in establishing the relevance of the majority of variants identified by next generation sequencing tests. Indeed, the majority of mutations identified are harbored by proteins whose functions remain elusive. Herein we describe the current scenario in genomic testing and in particular the burden of variants of uncertain significance (VUSs). We highlight a role for molecular modeling and molecular dynamic simulations as tools that can significantly increase the yield of information to aid in the evaluation of pathogenicity. Though the application of these methodologies to the interpretation of variants identified by genomic testing is not yet widespread, we predict that an increase in their use will significantly benefit the mission of clinical genomics for individualized medicine.

Development and Evaluation of a Smartphone Application for Managing Gestational Diabetes Mellitus

Objectives

The purpose of this study was to develop and evaluate an application (app) that provides tailored recommendations based on lifestyle and clinical data entered by the user.

Methods

Knowledge and functions required for the gestational diabetes mellitus (GDM) management app were extracted from clinical practice guidelines and evaluated through an online survey. Common and tailored recommendations were developed and evaluated with a content validity index. Algorithms to link tailored recommendations with a patient's data were developed and evaluated by experts. An Android-based app was developed and evaluated by comparing the process of data entry and recommendation retrieval and the usability of the app. After the app was revised, the user acceptance of the app was evaluated.

Results

Six domains of knowledge and 14 functions were extracted. Seven common and 49 tailored recommendations were developed. Nine lifestyle and clinical data elements were modeled. Eight algorithms with 18 decision nodes presenting tailored recommendations based on patient's data and 12 user interface screens were developed. All recommendations obtained from the use of app concurred with recommendations derived by algorithms. The average usability score was 69.5 out of 100. The user acceptance score with behavioral intention to use was 5.5, intrinsic motivation 4.3, the perceived ease of use score was 4.6, and the perceived usefulness score was 5.0 out of 7, respectively.

Conclusions

The GDM management knowledge and tailored recommendations obtained in this study could be of help in managing GDM.

Characterization of endoscopic ultrasound fine-needle aspiration cytology by targeted next-generation sequencing and theranostic potential

Determination of tumor genetic architecture based on tissue analysis yields important information on signaling pathways involved in cancer pathogenesis and plays a growing role in choosing the optimal medical management of malignancies. Specifically, the advent of next-generation sequencing has led to a rapidly evolving era of relatively inexpensive, high-throughput DNA sequencing of tumors. One such example is multiplexed tumor genotyping (ie, panel testing) of more than 2800 mutations across 50 commonly mutated cancer-associated genes. This resulting mutational landscape shows medically actionable pathogenic alterations to optimize antitumor therapy. We recently assessed the performance and outcome of targeted next-generation sequencing with archived endoscopic ultrasound fine-needle aspirates across a broad range of primary and metastatic sites with encouraging accuracy. As a result, endoscopic ultrasound has the potential to move from a test for diagnosis or confirmation of malignancy, to one in which it could facilitate the personalization of cancer-directed therapy.

Efficacy of bronchoscopic lung volume reduction by endobronchial valves in patients with heterogeneous emphysema: report on the first Asian cases

Although many patients with severe emphysema have benefited from bronchoscopic lung volume reduction (BLVR) worldwide, experience of BLVR in Asian emphysema patients is scarce. Between July 2012 and March 2013, seven patients with advanced heterogeneous emphysema underwent BLVR in the Asan Medical Center. They had severe dyspnea and poor lung function (Modified Medical Research Council dyspnea scale 3-4; median forced expiratory volume in 1 sec [FEV1], 0.59 L [19.0 % predicted]; median 6-min walk distance [6MWD], 195 m). Endobronchial valves were inserted into the target lobe which was most hyperinflated and least perfused, and had no collateral ventilation with other lobes. Six patients showed clinical improvement after 1 month. Of them, 2 patients improved to dyspnea scale 1 and 4 patients did to scale 2 (P = 0.026). The median FEV1 increased from 0.59 to 0.89 L (51%; P = 0.028) and the median 6MWD increased from 195 to 252 m (29.2%; P = 0.028). Two patients developed a pneumothorax (one requiring drainage) and one patient experienced slight hemoptysis; however, there were no other serious adverse events. BLVR is effective in Asian advanced emphysema patients, with noted clinical improvements in lung function and exercise capacity.

Genetic data and electronic health records: a discussion of ethical, logistical and technological considerations

Objective

The completion of sequencing the human genome in 2003 has spurred the production and collection of genetic data at ever increasing rates. Genetic data obtained for clinical purposes, as is true for all results of clinical tests, are expected to be included in patients’ medical records. With this explosion of information, questions of what, when, where and how to incorporate genetic data into electronic health records (EHRs) have reached a critical point. In order to answer these questions fully, this paper addresses the ethical, logistical and technological issues involved in incorporating these data into EHRs.

Materials and methods

This paper reviews journal articles, government documents and websites relevant to the ethics, genetics and informatics domains as they pertain to EHRs.

Results and discussion

The authors explore concerns and tasks facing health information technology (HIT) developers at the intersection of ethics, genetics, and technology as applied to EHR development.

Conclusions

By ensuring the efficient and effective incorporation of genetic data into EHRs, HIT developers will play a key role in facilitating the delivery of personalized medicine.

Longitudinal analysis of pain in patients with metastatic prostate cancer using natural language processing of medical record text

Objectives

To test the feasibility of using text mining to depict meaningfully the experience of pain in patients with metastatic prostate cancer, to identify novel pain phenotypes, and to propose methods for longitudinal visualization of pain status.

Materials and methods

Text from 4409 clinical encounters for 33 men enrolled in a 15-year longitudinal clinical/molecular autopsy study of metastatic prostate cancer (Project to ELIminate lethal CANcer) was subjected to natural language processing (NLP) using Unified Medical Language System-based terms. A four-tiered pain scale was developed, and logistic regression analysis identified factors that correlated with experience of severe pain during each month.

Results

NLP identified 6387 pain and 13 827 drug mentions in the text. Graphical displays revealed the pain ‘landscape’ described in the textual records and confirmed dramatically increasing levels of pain in the last years of life in all but two patients, all of whom died from metastatic cancer. Severe pain was associated with receipt of opioids (OR=6.6, p<0.0001) and palliative radiation (OR=3.4, p=0.0002). Surprisingly, no severe or controlled pain was detected in two of 33 subjects’ clinical records. Additionally, the NLP algorithm proved generalizable in an evaluation using a separate data source (889 Informatics for Integrating Biology and the Bedside (i2b2) discharge summaries).

Discussion

Patterns in the pain experience, undetectable without the use of NLP to mine the longitudinal clinical record, were consistent with clinical expectations, suggesting that meaningful NLP-based pain status monitoring is feasible. Findings in this initial cohort suggest that ‘outlier’ pain phenotypes useful for probing the molecular basis of cancer pain may exist.

Limitations

The results are limited by a small cohort size and use of proprietary NLP software.

Conclusions

We have established the feasibility of tracking longitudinal patterns of pain by text mining of free text clinical records. These methods may be useful for monitoring pain management and identifying novel cancer phenotypes.