-
Life Science Alliance Aug 2024Dynamic rearrangements of the F-actin cytoskeleton are a hallmark of tumor metastasis. Thus, proteins that govern F-actin rearrangements are of major interest for...
Dynamic rearrangements of the F-actin cytoskeleton are a hallmark of tumor metastasis. Thus, proteins that govern F-actin rearrangements are of major interest for understanding metastasis and potential therapies. We hypothesized that the unique F-actin binding and bundling protein SWAP-70 contributes importantly to metastasis. Orthotopic, ectopic, and short-term tail vein injection mouse breast and lung cancer models revealed a strong positive dependence of lung and bone metastasis on SWAP-70. Breast cancer cell growth, migration, adhesion, and invasion assays revealed SWAP-70's key role in these metastasis-related cell features and the requirement for SWAP-70 to bind F-actin. Biophysical experiments showed that tumor cell stiffness and deformability are negatively modulated by SWAP-70. Together, we present a hitherto undescribed, unique F-actin modulator as an important contributor to tumor metastasis.
Topics: Animals; Actins; Mice; Humans; Female; Cell Line, Tumor; Neoplasm Metastasis; Breast Neoplasms; Lung Neoplasms; Microfilament Proteins; Cell Movement; Actin Cytoskeleton; Cell Proliferation; Cell Adhesion; Protein Binding
PubMed: 38760173
DOI: 10.26508/lsa.202302307 -
BMJ Open May 2024The administration of immune checkpoint inhibitors (ICIs) may lead to renal adverse events, notably including renal dysfunction. To early predict the probability of...
Development and validation of a nomogram for predicting the occurrence of renal dysfunction after treatment of immune checkpoint inhibitor: a retrospective case-control study.
PURPOSE
The administration of immune checkpoint inhibitors (ICIs) may lead to renal adverse events, notably including renal dysfunction. To early predict the probability of renal dysfunction after ICIs therapy, a retrospective case-control study was conducted.
METHODS
Clinical information on ICIs-treated patients was collected. Multivariable logistic regression was applied to identify risk factors for renal dysfunction after ICIs treatment. Moreover, a nomogram model was developed and validated internally.
RESULTS
A total of 442 patients were included, among which 35 (7.9%) experienced renal dysfunction after ICIs treatment. Lower baseline estimated glomerular filtration rate (eGFR) (OR 0.941; 95% CI 0.917 to 0.966; p<0.001), concurrent exposure of platinum(OR 4.014; 95% CI 1.557 to 10.346; p=0.004), comorbidities of hypertension (OR 3.478; 95% CI 1.600 to 7.562; p=0.002) and infection (OR 5.402; 95% CI 1.544 to 18.904; p=0.008) were found to be independent associated with renal dysfunction after ICIs treatment. To develop a predictive nomogram for the occurrence of renal dysfunction after ICIs treatment, the included cases were divided into training and validation groups in a ratio of 7:3 randomly. The above four independent risk factors were included in the model. The area under the receiver operating characteristic curves of the predictiive model were 0.822 (0.723-0.922) and 0.815 (0.699-0.930) in the training and validation groups, respectively.
CONCLUSIONS
Lower baseline eGFR, platinum exposure, comorbidities of hypertension and infection were predictors of renal dysfunction in ICIs-treated patients with cancer. A nomogram was developed to predict the probability of renal dysfunction after ICIs treatment, which might be operable and valuable in clinical practice.
Topics: Humans; Nomograms; Male; Female; Retrospective Studies; Immune Checkpoint Inhibitors; Middle Aged; Case-Control Studies; Aged; Glomerular Filtration Rate; Risk Factors; Logistic Models; Neoplasms; Renal Insufficiency; Kidney Diseases
PubMed: 38760047
DOI: 10.1136/bmjopen-2023-082484 -
PloS One 2024Mechanisms underlying primary and acquired resistance to MET tyrosine kinase inhibitors (TKIs) in managing non-small cell lung cancer remain unclear. In this study, we...
Mechanisms underlying primary and acquired resistance to MET tyrosine kinase inhibitors (TKIs) in managing non-small cell lung cancer remain unclear. In this study, we investigated the possible mechanisms acquired for crizotinib in MET-amplified lung carcinoma cell lines. Two MET-amplified lung cancer cell lines, EBC-1 and H1993, were established for acquired resistance to MET-TKI crizotinib and were functionally elucidated. Genomic and transcriptomic data were used to assess the factors contributing to the resistance mechanism, and the alterations hypothesized to confer resistance were validated. Multiple mechanisms underlie acquired resistance to crizotinib in MET-amplified lung cancer cell lines. In EBC-1-derived resistant cells, the overexpression of SERPINE1, the gene encoding plasminogen activator inhibitor-1 (PAI-1), mediated the drug resistance mechanism. Crizotinib resistance was addressed by combination therapy with a PAI-1 inhibitor and PAI-1 knockdown. Another mechanism of resistance in different subline cells of EBC-1 was evaluated as epithelial-to-mesenchymal transition with the upregulation of antiapoptotic proteins. In H1993-derived resistant cells, MEK inhibitors could be a potential therapeutic strategy for overcoming resistance with downstream mitogen-activated protein kinase pathway activation. In this study, we revealed the different mechanisms of acquired resistance to the MET inhibitor crizotinib with potential therapeutic application in patients with MET-amplified lung carcinoma.
Topics: Humans; Plasminogen Activator Inhibitor 1; Carcinoma, Non-Small-Cell Lung; Drug Resistance, Neoplasm; Proto-Oncogene Proteins c-met; Crizotinib; Lung Neoplasms; Cell Line, Tumor; Protein Kinase Inhibitors; Epithelial-Mesenchymal Transition; Gene Expression Regulation, Neoplastic
PubMed: 38758826
DOI: 10.1371/journal.pone.0300644 -
PloS One 2024The workload of breast cancer pathological diagnosis is very heavy. The purpose of this study is to establish a nomogram model based on pathological images to predict...
BACKGROUND
The workload of breast cancer pathological diagnosis is very heavy. The purpose of this study is to establish a nomogram model based on pathological images to predict the benign and malignant nature of breast diseases and to validate its predictive performance.
METHODS
In retrospect, a total of 2,723 H&E-stained pathological images were collected from 1,474 patients at Qingdao Central Hospital between 2019 and 2022. The dataset consisted of 509 benign tumor images (adenosis and fibroadenoma) and 2,214 malignant tumor images (infiltrating ductal carcinoma). The images were divided into a training set (1,907) and a validation set (816). Python3.7 was used to extract the values of the R channel, G channel, B channel, and one-dimensional information entropy from all images. Multivariable logistic regression was used to select variables and establish the breast tissue pathological image prediction model.
RESULTS
The R channel value, B channel value, and one-dimensional information entropy of the images were identified as independent predictive factors for the classification of benign and malignant pathological images (P < 0.05). The area under the curve (AUC) of the nomogram model in the training set was 0.889 (95% CI: 0.869, 0.909), and the AUC in the validation set was 0.838 (95% CI: 0.7980.877). The calibration curve results showed that the calibration curve of this nomogram model was close to the ideal curve. The decision curve results indicated that the predictive model curve had a high value for auxiliary diagnosis.
CONCLUSION
The nomogram model for the prediction of benign and malignant breast diseases based on pathological images demonstrates good predictive performance. This model can assist in the diagnosis of breast tissue pathological images.
Topics: Humans; Female; Breast Neoplasms; Middle Aged; Adult; Nomograms; Fibroadenoma; Retrospective Studies; Breast; Aged
PubMed: 38758814
DOI: 10.1371/journal.pone.0294923 -
PloS One 2024The diagnosis of breast cancer through MicroWave Imaging (MWI) technology has been extensively researched over the past few decades. However, continuous improvements to...
The diagnosis of breast cancer through MicroWave Imaging (MWI) technology has been extensively researched over the past few decades. However, continuous improvements to systems are needed to achieve clinical viability. To this end, the numerical models employed in simulation studies need to be diversified, anatomically accurate, and also representative of the cases in clinical settings. Hence, we have created the first open-access repository of 3D anatomically accurate numerical models of the breast, derived from 3.0T Magnetic Resonance Images (MRI) of benign breast disease and breast cancer patients. The models include normal breast tissues (fat, fibroglandular, skin, and muscle tissues), and benign and cancerous breast tumors. The repository contains easily reconfigurable models which can be tumor-free or contain single or multiple tumors, allowing complex and realistic test scenarios needed for feasibility and performance assessment of MWI devices prior to experimental and clinical testing. It also includes an executable file which enables researchers to generate models incorporating the dielectric properties of breast tissues at a chosen frequency ranging from 3 to 10 GHz, thereby ensuring compatibility with a wide spectrum of research requirements and stages of development for any breast MWI prototype system. Currently, our dataset comprises MRI scans of 55 patients, but new exams will be continuously added.
Topics: Humans; Magnetic Resonance Imaging; Breast Neoplasms; Female; Breast; Microwave Imaging; Microwaves
PubMed: 38758760
DOI: 10.1371/journal.pone.0302974 -
BJS Open May 2024Breast-conserving surgery with adjuvant radiotherapy and mastectomy are currently offered as equivalent surgical options for early-stage breast cancer based on RCTs from... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Breast-conserving surgery with adjuvant radiotherapy and mastectomy are currently offered as equivalent surgical options for early-stage breast cancer based on RCTs from the 1970s and 1980s. However, the treatment of breast cancer has evolved and recent observational studies suggest a survival advantage for breast-conserving surgery with adjuvant radiotherapy. A systematic review and meta-analysis was undertaken to summarize the contemporary evidence regarding survival after breast-conserving surgery with adjuvant radiotherapy versus mastectomy for women with early-stage breast cancer.
METHODS
A systematic search of MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL), and Embase that identified studies published between 1 January 2000 and 18 December 2023 comparing overall survival after breast-conserving surgery with adjuvant radiotherapy versus mastectomy for patients with unilateral stage 1-3 breast cancer was undertaken. The main exclusion criteria were studies evaluating neoadjuvant chemotherapy, rare breast cancer subtypes, and specific breast cancer populations. The ROBINS-I tool was used to assess risk of bias, with the overall certainty of evidence assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) tool. Studies without critical risk of bias were included in a quantitative meta-analysis.
RESULTS
From 11 750 abstracts, 108 eligible articles were identified, with one article including two studies; 29 studies were excluded from the meta-analysis due to an overall critical risk of bias, 42 studies were excluded due to overlapping study populations, and three studies were excluded due to reporting incompatible results. A total of 35 observational studies reported survival outcomes for 909 077 patients (362 390 patients undergoing mastectomy and 546 687 patients undergoing breast-conserving surgery with adjuvant radiotherapy). The pooled HR was 0.72 (95% c.i. 0.68 to 0.75, P < 0.001), demonstrating improved overall survival for patients undergoing breast-conserving surgery with adjuvant radiotherapy. The overall certainty of the evidence was very low.
CONCLUSION
This meta-analysis provides evidence suggesting a survival advantage for women undergoing breast-conserving surgery with adjuvant radiotherapy for early-stage breast cancer compared with mastectomy. Although these results should be interpreted with caution, they should be shared with patients to support informed surgical decision-making.
Topics: Humans; Radiotherapy, Adjuvant; Female; Mastectomy, Segmental; Breast Neoplasms; Neoplasm Staging; Mastectomy
PubMed: 38758563
DOI: 10.1093/bjsopen/zrae040 -
JAMA Network Open May 2024Oral endocrine treatments have been shown to be effective when carefully adhered to. However, in patients with early breast cancer, adherence challenges are notable,...
IMPORTANCE
Oral endocrine treatments have been shown to be effective when carefully adhered to. However, in patients with early breast cancer, adherence challenges are notable, with 17% experiencing nonpersistence and 41% nonadherence at least once.
OBJECTIVE
To model the persistence of and adherence to oral anticancer treatment of a patient with localized breast cancer.
DESIGN, SETTING, AND PARTICIPANTS
This cohort study was conducted using anonymous reimbursement data belonging to French female patients with breast cancer, extracted from the French Health Insurance database from January 2013 to December 2018. Data analysis was conducted from January 2021 to May 2022.
MAIN OUTCOMES AND MEASURES
The main outcome was the detection of episodes of nonpersistence and nonadherence 6 months before they happened. Adherence was defined as the ratio between the time covered by a drug purchase and the time between 2 purchases; patients were considered nonadherent if the ratio of their next 3 purchases was less than 80%. Disparities in persistence and adherence based on criteria such as age, treatment type, and income were identified.
RESULTS
A total of 229 695 female patients (median [IQR] age, 63 [52-72] years) with localized breast cancer were included. A deep learning model based on a gated-recurrent unit architecture was used to detect episodes of nonpersistence or nonadherence. This model demonstrated an area under the receiving operating curve of 0.71 for persistence and 0.73 for adherence. Analyzing the Shapley Additive Explanations values also gave insights into the contribution of the different features over the model's decision. Patients older than 70 years, with past nonadherence, taking more than 1 treatment in the previous 3 months, and with low income had greater risk of episodes of nonpersistence. Age and past nonadherence, including regularity of past adherence, were also important features in the nonadherence model.
CONCLUSIONS AND RELEVANCE
This cohort study found associations of patient age and past adherence with nonpersistence or nonadherence. It also suggested that regular intervals in treatment purchases enhanced adherence, in contrast to irregular purchasing patterns. This research offers valuable tools for improving persistence of and adherence to oral anticancer treatment among patients with early breast cancer.
Topics: Humans; Breast Neoplasms; Female; Medication Adherence; Middle Aged; Aged; Cohort Studies; France; Antineoplastic Agents
PubMed: 38758553
DOI: 10.1001/jamanetworkopen.2024.11909 -
Integrative Cancer Therapies 2024Cancer-related fatigue and its associated symptoms of sleep disorder and depression are prevalent in cancer survivors especially among breast, lung, and colorectal... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Cancer-related fatigue and its associated symptoms of sleep disorder and depression are prevalent in cancer survivors especially among breast, lung, and colorectal cancer survivors. While there is no gold standard for treating cancer-related fatigue currently, studies of mind-body exercises such as Qigong have reported promise in reducing symptoms. This study was designed to evaluate the feasibility and effect of Guolin Qigong on cancer-related fatigue and other symptoms in breast, lung and colorectal cancer survivors while exploring their perceptions and experiences of Guolin Qigong intervention.
METHODS
This is an open-label randomized controlled trial with 60 participants divided into 2 study groups in a 1:1 ratio. The intervention group will receive 12 weeks of Guolin Qigong intervention with a 4-week follow-up while control will receive usual care under waitlist. The primary outcome will be feasibility measured based on recruitment and retention rates, class attendance, home practice adherence, nature, and quantum of missing data as well as safety. The secondary subjective outcomes of fatigue, sleep quality and depression will be measured at Week-1 (baseline), Week-6 (mid-intervention), Week-12 (post-intervention), and Week-16 (4 weeks post-intervention) while an objective 24-hour urine cortisol will be measured at Week-1 (baseline) and Week-12 (post-intervention). We will conduct a semi-structured interview individually with participants within 3 months after Week-16 (4 weeks post-intervention) to obtain a more comprehensive view of practice adherence.
DISCUSSION
This is the first mixed-method study to investigate the feasibility and effect of Guolin Qigong on breast, lung, and colorectal cancer survivors to provide a comprehensive understanding of Guolin Qigong's intervention impact and participants' perspectives. The interdisciplinary collaboration between Western Medicine and Chinese Medicine expertise of this study ensures robust study design, enhanced participant care, rigorous data analysis, and meaningful interpretation of results. This innovative research contributes to the field of oncology and may guide future evidence-based mind-body interventions to improve cancer survivorship.
TRIAL REGISTRATION
This study has been registered with ANZCTR (ACTRN12622000688785p), was approved by Medical Research Ethic Committee of University Malaya Medical Centre (MREC ID NO: 2022323-11092) and recognized by Western Sydney University Human Research Ethics Committee (RH15124).
Topics: Humans; Qigong; Cancer Survivors; Fatigue; Female; Depression; Quality of Life; Neoplasms; Mind-Body Therapies; Male; Middle Aged; Adult; Randomized Controlled Trials as Topic; Sleep Wake Disorders; Sleep Quality
PubMed: 38757745
DOI: 10.1177/15347354241252698 -
Archives of Medical Science : AMS 2024Invasive micropapillary carcinoma (IMPC) treatment only relies on the standard treatment of nonspecific invasive breast cancer (NSIBC), and it remains controversial...
INTRODUCTION
Invasive micropapillary carcinoma (IMPC) treatment only relies on the standard treatment of nonspecific invasive breast cancer (NSIBC), and it remains controversial whether the survival of patients improves. Therefore, this study aimed to analyze the clinicopathological features of IMPC and to investigate the factors affecting its prognosis.
MATERIAL AND METHODS
This retrospective cohort study included 104 IMPC patients who met the study's inclusion criteria out of a total of 4,532 patients with invasive breast cancer between January 2015 and December 2019. A contemporaneous cohort of 230 patients with non-specific invasive breast cancer (NSIBC) who underwent surgery was identified and matched using propensity scores.
RESULTS
The survival rate for patients with IMPC ranged from 1.12% to 7.03%. Statistically significant differences were observed in the proportion of endocrine treatment, lymphatic invasion, estrogen receptor (ER)-positive rate, molecular subtypes, molecular typing, and 5-year loco-regional recurrence-free survival (LRRFS) between the two cohorts ( < 0.05). The univariate analysis showed that T stage, N stage, lymphatic invasion, vascular invasion, ER-positive rate, and progesterone receptor (PR)-negative rate were all prognosis risk factors ( < 0.05) for IMPC. Furthermore, the multivariate analysis indicated that lymphatic invasion and N stage were independent prognostic factors ( < 0.05).
CONCLUSIONS
The incidence of micropapillary IMPC, among other pathological subtypes, is steadily increasing. ER-positive and PR-positive rates, as well as luminal subtypes, are frequent, with a concurrent increase in the 5-year locoregional recurrence rate. It would be interesting to compare the effect following these therapeutic modifications in larger cohorts in future studies.
PubMed: 38757040
DOI: 10.5114/aoms/173213 -
Frontiers in Immunology 2024This study aims to identify precise biomarkers for breast cancer to improve patient outcomes, addressing the limitations of traditional staging in predicting treatment...
BACKGROUND
This study aims to identify precise biomarkers for breast cancer to improve patient outcomes, addressing the limitations of traditional staging in predicting treatment responses.
METHODS
Our analysis encompassed data from over 7,000 breast cancer patients across 14 datasets, which included in-house clinical data and single-cell data from 8 patients (totaling 43,766 cells). We utilized an integrative approach, applying 10 machine learning algorithms in 54 unique combinations to analyze 100 existing breast cancer signatures. Immunohistochemistry assays were performed for empirical validation. The study also investigated potential immunotherapies and chemotherapies.
RESULTS
Our research identified five consistent glutamine metabolic reprogramming (GMR)-related genes from multi-center cohorts, forming the foundation of a novel GMR-model. This model demonstrated superior accuracy in predicting recurrence and mortality risks compared to existing clinical and molecular features. Patients classified as high-risk by the model exhibited poorer outcomes. IHC validation in 30 patients reinforced these findings, suggesting the model's broad applicability. Intriguingly, the model indicates a differential therapeutic response: low-risk patients may benefit more from immunotherapy, whereas high-risk patients showed sensitivity to specific chemotherapies like BI-2536 and ispinesib.
CONCLUSIONS
The GMR-model marks a significant leap forward in breast cancer prognosis and the personalization of treatment strategies, offering vital insights for the effective management of diverse breast cancer patient populations.
Topics: Humans; Breast Neoplasms; Female; Machine Learning; Glutamine; Biomarkers, Tumor; Prognosis; Gene Expression Regulation, Neoplastic; Middle Aged; Transcriptome; Metabolic Reprogramming
PubMed: 38756785
DOI: 10.3389/fimmu.2024.1369289