...these genomic changes are largely unknown to practicing pathologists. ...Zhang et al discuss the emerging cancer biomarkers and provide a molecular genetic update in tumors of bone, solid, soft, ...hematopoietic, and lymphoid tissues. Classification of endometrial carcinomas can be a diagnostic challenge. ...4 distinct molecular subtypes with different prognostic values have been proposed by the Cancer Genome Atlas program and are being adopted by an increased number of pathologists and oncologists. ...the updates on the IHC and molecular classification of endometrial carcinoma by Wang et al are timely and clinically relevant.
Most biomedical datasets, including those of ‘omics, population studies, and surveys, are rectangular in shape and have few missing data. Recently, their sample sizes have grown significantly. ...Rigorous analyses on these large datasets demand considerably more efficient and more accurate algorithms. Machine learning (ML) algorithms have been used to classify outcomes in biomedical datasets, including random forests (RF), decision tree (DT), artificial neural networks (ANN), and support vector machine (SVM). However, their performance and efficiency in classifying multi-category outcomes of rectangular data are poorly understood. Therefore, we compared these metrics among the 4 ML algorithms. As an example, we created a large rectangular dataset using the female breast cancers in the surveillance, epidemiology, and end results-18 database, which were diagnosed in 2004 and followed up until December 2016. The outcome was the five-category cause of death, namely alive, non-breast cancer, breast cancer, cardiovascular disease, and other cause. We analyzed the 54 dichotomized features from ~45,000 patients using MatLab (version 2018a) and the tenfold cross-validation approach. The accuracy in classifying five-category cause of death with DT, RF, ANN, and SVM was 69.21%, 70.23%, 70.16%, and 69.06%, respectively, which was higher than the accuracy of 68.12% with multinomial logistic regression. Based on the features' information entropy, we optimized dimension reduction (i.e., reduce the number of features in models). We found 32 or more features were required to maintain similar accuracy, while the running time decreased from 55.57 s for 54 features to 25.99 s for 32 features in RF, from 12.92 s to 10.48 s in ANN, and from 175.50 s to 67.81 s in SVM. In summary, we here show that RF, DT, ANN, and SVM had similar accuracy for classifying multi-category outcomes in this large rectangular dataset. Dimension reduction based on information gain will increase the model's efficiency while maintaining classification accuracy.
Colorectal cancer (CRC) is one of the most common cancers worldwide, and a leading cause of cancer deaths. Better classifying multicategory outcomes of CRC with clinical and omic data may help adjust ...treatment regimens based on individual's risk. Here, we selected the features that were useful for classifying four-category survival outcome of CRC using the clinical and transcriptomic data, or clinical, transcriptomic, microsatellite instability and selected oncogenic-driver data (all data) of TCGA. We also optimized multimetric feature selection to develop the best multinomial logistic regression (MLR) and random forest (RF) models that had the highest accuracy, precision, recall and F1 score, respectively. We identified 2073 differentially expressed genes of the TCGA RNASeq dataset. MLR overall outperformed RF in the multimetric feature selection. In both RF and MLR models, precision, recall and F1 score increased as the feature number increased and peaked at the feature number of 600–1000, while the models' accuracy remained stable. The best model was the MLR one with 825 features based on sum of squared coefficients using all data, and attained the best accuracy of 0.855, F1 of 0.738 and precision of 0.832, which were higher than those using clinical and transcriptomic data. The top-ranked features in the MLR model of the best performance using clinical and transcriptomic data were different from those using all data. However, pathologic staging, HBS1L, TSPYL4, and TP53TG3B were the overlapping top-20 ranked features in the best models using clinical and transcriptomic, or all data. Thus, we developed a multimetric feature-selection based MLR model that outperformed RF models in classifying four-category outcome of CRC patients. Interestingly, adding microsatellite instability and oncogenic-driver data to clinical and transcriptomic data improved models' performances. Precision and recall of tuned algorithms may change significantly as the feature number changes, but accuracy appears not sensitive to these changes.
Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models
It is unclear how to best classify cancer outcomes using ‘omic data. We developed a multimetric feature-selection based multinomial logistic regression model that outperformed random forest models in classifying 4-category outcome of colorectal cancer. Adding microsatellite instability and oncogenic-driver data to clinical and transcriptomic data improves models' performances, with pathologic staging, HBS1L, TSPYL4, and TP53TG3B as important features. Interestingly, precision and recall of tuned algorithms change as the feature number changes, but accuracy does not.
The Oncotype DX breast recurrence score has been introduced more than a decade ago to aid physicians in determining the need for systemic adjuvant chemotherapy in patients with early-stage, estrogen ...receptor (ER)+, lymph node-negative breast cancer.
In this study, we utilized data from The Surveillance, Epidemiology, and End Results (SEER) Program to investigate temporal trends in Oncotype DX usage among US breast cancer patients in the first decade after the introduction of the Oncotype DX assay.
We found that the use of Oncotype DX has steadily increased in the first decade of use and that this increase is associated with a decreased usage of chemotherapy. Patients who utilized the Oncotype DX test tended to have improved survival compared to patients who did not use the assay even after adjusting for clinical variables associated with prognosis. In addition, chemotherapy usage in patients with high-risk scores is associated with significantly longer overall and breast cancer-specific survival compared to high-risk patients who did not receive chemotherapy. On the contrary, patients with low-risk scores who were treated with chemotherapy tended to have shorter overall survival compared to low-risk patients who forwent chemotherapy.
We have provided a comprehensive temporal overview of the use of Oncotype DX in breast cancer patients in the first decade after Oncotype DX was introduced. Our results suggest that the use of Oncotype DX is increasing in ER+ breast cancer and that the Oncotype DX test results provide valuable information for patient treatment and prognosis.
Paneth cells are residents of the intestinal epithelium. Abnormal appearance of Paneth cells has been widely documented in non-intestinal tissues within the digestive tract and even observed in ...non-gastrointestinal organs. Although metaplastic Paneth cells are part of the overarching pathology of intestinal metaplasia (IM), only a fraction of intestinal metaplastic lesions contain Paneth cells. We survey literature documenting metaplastic Paneth cells to gain insights into mechanism underlying their etiologic development as well as their potential relevance to human health. A synthesized view from this study suggests that the emergence of metaplastic Paneth cells at extra-intestinal mucosal sites likely represents a protective, anti-bacterial, and inflammatory response evoked by an altered microbial activity.
Triple-negative breast cancer (TNBC) patients have the worst prognosis and distant metastasis-free survival among all major subtypes of breast cancer. The poor clinical outlook is further exacerbated ...by a lack of effective targeted therapies for TNBC. Here we show that ectopic expression and therapeutic delivery of the secreted protein Tubulointerstitial nephritis antigen-like 1 (Tinagl1) suppresses TNBC progression and metastasis through direct binding to integrin α5β1, αvβ1, and epidermal growth factor receptor (EGFR), and subsequent simultaneous inhibition of focal adhesion kinase (FAK) and EGFR signaling pathways. Moreover, Tinagl1 protein level is associated with good prognosis and reversely correlates with FAK and EGFR activation status in TNBC. Our results suggest Tinagl1 as a candidate therapeutic agent for TNBC by dual inhibition of integrin/FAK and EGFR signaling pathways.
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•Endogenous and recombinant Tinagl1 suppress growth and metastasis of breast cancer•Tinagl1 inhibits EGFR and integrin/FAK activation through distinct mechanisms•Tinagl1 level negatively correlates with EGFR and FAK activation in TNBC•Tinagl1 is a good prognosis marker and candidate therapeutic agent for TNBC
Shen et al. show that Tinagl1 suppresses triple-negative breast cancer (TNBC) by inhibiting FAK and EGFR signaling pathways simultaneously via binding to integrin α5β1, αvβ1, and EGFR. The Tinagl1 protein level is associated with good prognosis and inversely correlates with FAK and EGFR activation status in TNBC.
The role of p53 in tumor suppression has been extensively studied and well-established. However, the role of p53 in parasitic infections and the intestinal type 2 immunity is unclear. Here, we report ...that p53 is crucial for intestinal type 2 immunity in response to the infection of parasites, such as Tritrichomonas muris and Nippostrongylus brasiliensis. Mechanistically, p53 plays a critical role in the activation of the tuft cell-IL-25-type 2 innate lymphoid cell circuit, partly via transcriptional regulation of Lrmp in tuft cells. Lrmp modulates Ca
influx and IL-25 release, which are critical triggers of type 2 innate lymphoid cell response. Our results thus reveal a previously unrecognized function of p53 in regulating intestinal type 2 immunity to protect against parasitic infections, highlighting the role of p53 as a guardian of immune integrity.
The tumor suppressor TP53 is the most frequently mutated gene in human cancers. Mutant p53 (mutp53) proteins often accumulate to very high levels in human cancers to promote cancer progression ...through the gain-of-function (GOF) mechanism. Currently, the mechanism underlying mutp53 accumulation and GOF is incompletely understood. Here, we identified TRIM21 as a critical E3 ubiquitin ligase of mutp53 by screening for specific mutp53-interacting proteins. TRIM21 directly interacted with mutp53 but not WT p53, resulting in ubiquitination and degradation of mutp53 to suppress mutp53 GOF in tumorigenesis. TRIM21 deficiency in cancer cells promoted mutp53 accumulation and GOF in tumorigenesis. Compared with p53R172H knockin mice, which displayed mutp53 accumulation specifically in tumors but not normal tissues, TRIM21 deletion in p53R172H knockin mice resulted in mutp53 accumulation in normal tissues, an earlier tumor onset, and a shortened life span of mice. Furthermore, TRIM21 was frequently downregulated in some human cancers, including colorectal and breast cancers, and low TRIM21 expression was associated with poor prognosis in patients with cancers carrying mutp53. Our results revealed a critical mechanism underlying mutp53 accumulation in cancers and also uncovered an important tumor-suppressive function of TRIM21 and its mechanism in cancers carrying mutp53.
Emerging evidence has suggested that the capability of a tumor to grow and propagate is dependent on a small subset of cells within a tumor, termed cancer stem cells. Although data have been provided ...to support this theory in human blood, brain, and breast cancers, the identity of pancreatic cancer stem cells has not been determined. Using a xenograft model in which primary human pancreatic adenocarcinomas were grown in immunocompromised mice, we identified a highly tumorigenic subpopulation of pancreatic cancer cells expressing the cell surface markers CD44, CD24, and epithelial-specific antigen (ESA). Pancreatic cancer cells with the CD44(+)CD24(+)ESA(+) phenotype (0.2-0.8% of pancreatic cancer cells) had a 100-fold increased tumorigenic potential compared with nontumorigenic cancer cells, with 50% of animals injected with as few as 100 CD44(+)CD24(+)ESA(+) cells forming tumors that were histologically indistinguishable from the human tumors from which they originated. The enhanced ability of CD44(+)CD24(+)ESA(+) pancreatic cancer cells to form tumors was confirmed in an orthotopic pancreatic tail injection model. The CD44(+)CD24(+)ESA(+) pancreatic cancer cells showed the stem cell properties of self-renewal, the ability to produce differentiated progeny, and increased expression of the developmental signaling molecule sonic hedgehog. Identification of pancreatic cancer stem cells and further elucidation of the signaling pathways that regulate their growth and survival may provide novel therapeutic approaches to treat pancreatic cancer, which is notoriously resistant to standard chemotherapy and radiation.
Universal Zero-Markup Drug Policy (UZMDP) mandates no price mark-ups on any drug dispensed by a healthcare institution, and covers the medicines not included in the China's National Essential ...Medicine System. Five tertiary hospitals in Beijing, China implemented UZMDP in 2012. Its impacts on these hospitals are unknown. We described the effects of UZMDP on a participating hospital, Jishuitan Hospital, Beijing, China (JST).
This retrospective longitudinal study examined the hospital-level data of JST and city-level data of tertiary hospitals of Beijing, China (BJT) 2009-2015. Rank-sum tests and join-point regression analyses were used to assess absolute changes and differences in trends, respectively.
In absolute terms, after the UZDMP implementation, there were increased annual patient-visits and decreased ratios of medicine-to-healthcare-charges (RMOH) in JST outpatient and inpatient services; however, in outpatient service, physician work-days decreased and physician-workload and inflation-adjusted per-visit healthcare charges increased, while the inpatient physician work-days increased and inpatient mortality-rate reduced. Interestingly, the decreasing trend in inpatient mortality-rate was neutralized after UZDMP implementation. Compared with BJT and under influence of UZDMP, JST outpatient and inpatient services both had increasing trends in annual patient-visits (annual percentage changesAPC = 8.1% and 6.5%, respectively) and decreasing trends in RMOH (APC = -4.3% and -5.4%, respectively), while JST outpatient services had increasing trend in inflation-adjusted per-visit healthcare charges (APC = 3.4%) and JST inpatient service had decreasing trend in inflation-adjusted per-visit medicine-charges (APC = -5.2%).
Implementation of UZMDP seems to increase annual patient-visits, reduce RMOH and have different impacts on outpatient and inpatient services in a Chinese urban tertiary hospital.
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