Low expression of TOX predicts poor prognosis of patients with breast cancer in the real world: A retrospective study.

Background: TOX is a transcription factor that is implicated in the regulation of T cell exhaustion in tumors. TOX has been proven to have prognostic value in some malignant tumors. We aim to analyze the expression of TOX in breast cancer patients, and the association between TOX and prognostic significance in patients with breast cancer.

The prediction of pCR and chemosensitivity for breast cancer patients using DLG3, RADL and Pathomics signatures based on machine learning and deep learning.

Background: Limited studies have investigated the predictive value of multiomics signatures (radiomics, deep learning features, pathological features and DLG3) in breast cancer patients who underwent neoadjuvant chemotherapy (NAC). However, no study has explored the relationships among radiomic, pathomic signatures and chemosensitivity. This study aimed to predict pathological complete response (pCR) using multiomics signatures, and to evaluate the predictive utility of radiomic and pathomic signatures for guiding chemotherapy selection.

Naples score: a novel prognostic biomarker for breast cancer patients undergoing neoadjuvant chemotherapy.

Background And Purpose: The Naples Score (NPS) is a novel prognostic indicator that has been used in various cancers, but its potential in breast malignant tumor patients receiving neoadjuvant chemotherapy (NAC) has not been discovered. This study aimed to investigate the relationship between NPS and overall survival (OS) and disease-free survival (DFS) in breast cancer patients.

Methods: A total of 217 breast cancer patients undergoing NAC were incorporated into this retrospectively research.

Clinicopathological Characteristics of Breast Cancer Patients with HER-2 Low Expression Receiving Neoadjuvant Therapy.

Introduction: Human epidermal growth factor receptor-2 (HER-2) low expression breast malignant tumors have become a research hotspot in recent years, but it is still unclear whether HER-2 low expression represents a special subtype of breast cancer. However, this molecular type requires more effective treatment regimens in the neoadjuvant therapy stage.

Methods: This study enrolled breast cancer patients who were treated at Harbin Medical University Cancer Hospital with neoadjuvant treatment between October 2011 and May 2019 and was a single-center retrospective study.

Prediction of nonsentinel lymph node metastasis in breast cancer patients based on machine learning.

Background: Develop the best machine learning (ML) model to predict nonsentinel lymph node metastases (NSLNM) in breast cancer patients.

Methods: From June 2016 to August 2022, 1005 breast cancer patients were included in this retrospective study. Univariate and multivariate analyses were performed using logistic regression.

A Novel Inflammatory and Nutritional Prognostic Scoring System for Nonpathological Complete Response Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy.

Background: It has been demonstrated that inflammatory and nutritional variables are associated with poor breast cancer survival. However, some studies do not include these variables due to missing data. To investigate the predictive potential of the INPS, we constructed a novel inflammatory-nutritional prognostic scoring (INPS) system with machine learning.

Prognostic value of a modified systemic inflammation score in breast cancer patients who underwent neoadjuvant chemotherapy.

Background And Purpose: The modified systemic inflammation score (mSIS) system, which is constructed based on the neutrophil to lymphocyte ratio (NLR) and albumin (Alb), has not been applied to evaluate the prognosis of malignant breast cancer patients who underwent neoadjuvant chemotherapy (NAC). The present study aimed to explore the relationship between the mSIS and overall survival (OS), disease-free survival (DFS) and pathological complete response (pCR).

Methods: A total of 305 malignant breast tumor patients who underwent NAC were incorporated into this retrospective analysis.

Prognostic factors for IB2-IIIB cervical cancer patients treated by radiation therapy with high-dose-rate brachytherapy in a single-institution study.

Purpose: To evaluate the efficacy of radiotherapy in locally advanced cervical cancer, and to determine the factors affecting prognosis.

Material And Methods: Clinical data of 211 patients with cervical cancer, treated at our institution between June 2014 and February 2017 were reviewed retrospectively. All patients were treated with definitive radiotherapy and received external irradiation of 45-50.

Prediction of lymph node metastasis in patients with breast invasive micropapillary carcinoma based on machine learning and SHapley Additive exPlanations framework.

Abstract: Background and purpose: Machine learning (ML) is applied for outcome prediction and treatment support. This study aims to develop different ML models to predict risk of axillary lymph node metastasis (LNM) in breast invasive micropapillary carcinoma (IMPC) and to explore the risk factors of LNM.

Methods: From the Surveillance, Epidemiology, and End Results (SEER) database and the records of our hospital, a total of 1547 patients diagnosed with breast IMPC were incorporated in this study.

The Pretreatment Systemic Inflammation Response Index as a Useful Prognostic Factor is Better Than Lymphocyte to Monocyte Ratio in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.

It has been reported that the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and lymphocyte to monocyte ratio (LMR), as well as systemic inflammation response index (SIRI), are closely related with overall survival (OS) in breast cancer patients. However, which one is the optimal indicator is vague. This study incorporates 280 breast cancer patients who received NACT.

Diagnostic Value of the Survivin Autoantibody in Four Types of Malignancies.

Background: Tumor-associated antigen overexpression, which has been reported in many types of cancers, may trigger autoantibody secretion. The present study was designed to test whether levels of circulating autoantibodies to survivin protein-derived antigens is altered in liver, esophageal, breast, and lung cancers.

Methods: Patients with liver (144), esophageal (159), breast (124), and lung cancers (267), and healthy volunteers (362) were recruited for the study, and serum samples were collected for ELISA autoantibody analysis.