Notes

Little Sternotomy and also Little Thoracotomy regarding Aortic Device Substitution: Is There a Big difference?
Philadelphia chromosome positive (Ph+) in T-lineage acute lymphoproliferative tumors is a rare event in both children and adults. In particular, it has not been reported in T-cell lymphoblastic lymphoma(T-LBL) yet. Here, we describe a patient with Ph+ T-LBL for both cytogenetic abnormality and BCR-ABL1 fusion transcript. Moreover, we review the published cases of Ph+ T-cell acute lymphoblastic leukemia (T-ALL) in the literature and summarize their clinical characteristics, management, and prognosis.
Due to the rarity of metaplastic breast carcinoma (MpBC), no randomized trials have investigated the role of combined chemotherapy and radiotherapy (CCRP) in this condition. We aimed to explore and identify the effectiveness of CCRP in patients with regional lymph node metastasis (N+) non-metastatic MpBC.

Data were obtained from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program database. We assessed the effects of CCRP on overall survival (OS), breast cancer-specific survival (BCSS), and breast cancer-specific death (BCSD) using Kaplan-Meier analysis, competing risk model analysis, and competing risk regression mode analysis.

A total of 707 women and 361 death cases were included in the unmatched cohort, of which 76.45% (276/361) were BCSD, and 23.55% (85/361) were non-breast cancer-specific deaths (non-BCSD). Both the ChemT and CCRP groups had better OS (ChemT group HR 0.59, 95% CI 0.45-0.78,
<0.001; CCRP group HR 0.31, 95% CI 0.23-0.41,
<0.001) and BCSS (ChemT group HR 0.63, 95% CI 0.45-0.87,
<0.001; CCRP group HR 0.32, 95%CI 0.22-0.46,
<0.001) than the non-therapy group. Subjects in the CCRP group tended to have significantly lower cumulative BCSD (Gray's test,
=0.001) and non-BCSD (Gray's test,
<0.001) than the non-therapy group or ChemT group. In competing risk regression model analysis, subjects in the CCRP group had a better prognosis in BCSD (HR 0.710, 95% CI 0.508-0.993,
=0.045) rather than the ChemT group (HR 1.081, 95% CI 0.761-1.535,
=0.660) than the non-therapy group.

Our study demonstrated that CCRP could significantly decrease the risk of death forboth BCSD and non-BCSD and provided a valid therapeutic strategy for patients with N+ non-metastatic MpBC.
Our study demonstrated that CCRP could significantly decrease the risk of death for both BCSD and non-BCSD and provided a valid therapeutic strategy for patients with N+ non-metastatic MpBC.Malignancies of alimentary tract include esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). Despite of their similarities in cancer development and progression, there are numerous researches concentrating on single tumor but relatively little on their common mechanisms. Our study explored the transcriptomic data of digestive tract cancers from The Cancer Genome Atlas database, yielding their common differentially expressed genes including 1,700 mRNAs, 29 miRNAs, and 362 long non-coding RNAs (lncRNAs). There were 12 mRNAs, 5 miRNAs, and 16 lncRNAs in the core competitive endogenous RNAs network by RNA-RNA interactions, highlighting the prognostic nodes of SERPINE1, hsa-mir-145, and SNHG1. In addition, the weighted gene co-expression network analysis (WGCNA) illustrated 20 gene modules associated with clinical traits. check details By taking intersections of modules related to the same trait, we got 67 common genes shared by ESCA and READ and screened 5 hub genes, including ADCY6, CXCL3, NPBWR1, TAS2R38, and PTGDR2. In conclusion, the present study found that SERPINE1/has-mir-145/SNHG1 axis acted as promising targets and the hub genes reasoned the similarity between ESCA and READ, which revealed the homogeneous tumorigenicity of digestive tract cancers at the transcriptome level and led to further comprehension and therapeutics for digestive tract cancers.
Currently, the prognostic performance of the staging systems proposed by the 8th edition of the American Joint Committee on Cancer (AJCC 8th) and the Liver Cancer Study Group of Japan (LCSGJ) in resectable intrahepatic cholangiocarcinoma (ICC) remains controversial. The aim of this study was to use machine learning techniques to modify existing ICC staging strategies based on clinical data and to demonstrate the accuracy and discrimination capacity in prognostic prediction.

This is a retrospective study based on 1,390 patients who underwent surgical resection for ICC at Eastern Hepatobiliary Surgery Hospital from 2007 to 2015. External validation was performed for patients from 2015 to 2017. The ensemble of three machine learning algorithms was used to select the most important prognostic factors and stepwise Cox regression was employed to derive a modified scoring system. The discriminative ability and predictive accuracy were assessed using the Concordance Index (C-index) and Brier Score (BS). The resulased on prognosis factors selection incorporated with machine learning, for individualized prognosis evaluation in patients with ICC.
This study put forward a modified ICC scoring system based on prognosis factors selection incorporated with machine learning, for individualized prognosis evaluation in patients with ICC.
Triple-negative breast cancer (TNBC) is considered to be higher grade, more aggressive and have a poorer prognosis than other types of breast cancer. Discover biomarkers in TNBC for risk stratification and treatments that improve prognosis are in dire need.

Clinical data of 195 patients with triple negative breast cancer confirmed by pathological examination and received neoadjuvant chemotherapy (NAC) were collected. The expression levels of EGFR and CK5/6 were measured before and after NAC, and the relationship between EGFR and CK5/6 expression and its effect on prognosis of chemotherapy was analyzed.

The overall response rate (ORR) was 86.2% and the pathological complete remission rate (pCR) was 29.2%. Univariate and multivariate logistic regression analysis showed that cT (clinical Tumor stages) stage was an independent factor affecting chemotherapy outcome. Multivariate Cox regression analysis showed pCR, chemotherapy effect, ypT, ypN, histological grades, and post- NAC expression of CK5/6 significantly affected prognosis.
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