Neoadjuvant pegylated liposomal doxorubicin- and epirubicin-based combination therapy regimens for early breast cancer: a multicenter retrospective case-control study.

PURPOSE: This study aimed to compare the effectiveness and safety of pegylated liposomal doxorubicin (PLD)-based and epirubicin-based combination therapy regimen as neoadjuvant therapy for early breast cancer. METHODS: Patients with stage I-III breast cancer who underwent neoadjuvant therapy followed by surgery between January 2018 and December 2019 were retrospectively reviewed. The primary outcome was pathological complete response (pCR) rate. The secondary outcome was radiologic complete response (rCR) rate. Outcomes were compared between treatment groups PLD-cyclophosphamide followed by docetaxel (LC-T group) or epirubicin-cyclophosphamide followed by docetaxel (EC-T group), using both propensity-score matched (matched) and unmatched data. RESULTS: Data were analyzed from patients who received neoadjuvant LC-T (n = 178) or EC-T (n = 181) treatment. The overall pCR rate and rCR rate were higher in the LC-T group compared with the EC-T group (unmatched pCR: 25.3% vs. 15.5%, p = 0.026; rCR: 14.7% vs. 6.7%, p = 0.016; matched pCR: 26.9% vs. 16.1%, p = 0.034; rCR: 15.5% vs. 7.4%, p = 0.044). Analysis by molecular subtype showed that compared with EC-T treatment, LC-T treatment achieved significantly greater pCR rate in triple-negative subtype and greater rCR rate in Her2 (+) subtype. CONCLUSIONS: Neoadjuvant PLD-based therapy may be a potential option for patients with early-stage breast cancer. The current results warrant further investigation.

Lidocaine transdermal patches reduced pain intensity in neuropathic cancer patients already receiving opioid treatment.

BACKGROUND: Limited efficacy has been observed when using opioids to treat neuropathic pain. Lidocaine patches reduce neuropathic pain in postherpetic neuralgia, but their benefits for cancer-related neuropathic pain remain unclear. This study aimed to investigate a treatment for cancer-related neuropathic pain. METHODS: We conducted a prospective, open-label, single-arm study to assess the efficacy and safety of lidocaine transdermal patches in patients experiencing localized, superficial, neuropathic cancer pain. Terminal cancer patients already receiving opioid treatment participated in the 3-day study. The primary endpoint was pain intensity evaluated by the numerical rating scale (NRS). The secondary endpoints were the pain relief score and the quality of analgesic treatment. RESULTS: The results showed a significant difference in the median NRS over 3 days (Kruskal-Wallis test, p < 0.0001). The median NRS pain intensity from Day 1 to Day 3 was 4.0 with 95% C.I. (3.3, 5.0), 3.0 (2.5, 3.5), and 2.6 (2.0, 3.0), respectively. The difference between the median NRS pain intensities of any 2 days was significant (Wilcoxon signed-rank test, p < 0.0001). The generalized estimating equation (GEE) estimation model showed significant differences between the NRS pain intensities on any 2 days. There was no significant difference in the pain relief score or the quality of analgesic treatment. CONCLUSIONS: In this study, the 5% lidocaine transdermal patch reduced the NRS pain intensity in neuropathic cancer patients already receiving opioid treatment. Treatment of localized and superficial neuropathic pain caused by cancer was well tolerated and effective.

Brain biopsy-proven intravascular lymphomatosis presenting as rapidly recurrent strokes-two case reports.

PURPOSE: Intravascular lymphomatosis (IVL) is rare and usually goes undiagnosed until the time of autopsy because of its protean neurological manifestations. CASE REPORT: In this report, we describe two women who developed rapidly recurrent strokes within one to two months. In both cases, brain magnetic resonance imaging showed progression of bilateral cerebral infarcts, and histopathology from brain biopsy confirmed the diagnosis of IVL. The first case did not receive chemotherapy and died of septic shock one month after diagnosis. The second case received whole brain radiotherapy followed by rituximab-containing chemotherapy, and experienced partial improvement of neurological deficits. However, she began to deteriorate in consciousness at 8 months and became stuporous at 10 months after the onset of symptoms. CONCLUSION: IVL should be considered as a possible etiology if multiple strokes occur in a short period of time.

A deep learning-based pipeline for analyzing the influences of interfacial mechanochemical microenvironments on spheroid invasion using differential interference contrast microscopic images.

Metastasis is the leading cause of cancer-related deaths. During this process, cancer cells are likely to navigate discrete tissue-tissue interfaces, enabling them to infiltrate and spread throughout the body. Three-dimensional (3D) spheroid modeling is receiving more attention due to its strengths in studying the invasive behavior of metastatic cancer cells. While microscopy is a conventional approach for investigating 3D invasion, post-invasion image analysis, which is a time-consuming process, remains a significant challenge for researchers. In this study, we presented an image processing pipeline that utilized a deep learning (DL) solution, with an encoder-decoder architecture, to assess and characterize the invasion dynamics of tumor spheroids. The developed models, equipped with feature extraction and measurement capabilities, could be successfully utilized for the automated segmentation of the invasive protrusions as well as the core region of spheroids situated within interfacial microenvironments with distinct mechanochemical factors. Our findings suggest that a combination of the spheroid culture and DL-based image analysis enable identification of time-lapse migratory patterns for tumor spheroids above matrix-substrate interfaces, thus paving the foundation for delineating the mechanism of local invasion during cancer metastasis.

Binary particle swarm optimization for operon prediction.

An operon is a fundamental unit of transcription and contains specific functional genes for the construction and regulation of networks at the entire genome level. The correct prediction of operons is vital for understanding gene regulations and functions in newly sequenced genomes. As experimental methods for operon detection tend to be nontrivial and time consuming, various methods for operon prediction have been proposed in the literature. In this study, a binary particle swarm optimization is used for operon prediction in bacterial genomes. The intergenic distance, participation in the same metabolic pathway, the cluster of orthologous groups, the gene length ratio and the operon length are used to design a fitness function. We trained the proper values on the Escherichia coli genome, and used the above five properties to implement feature selection. Finally, our study used the intergenic distance, metabolic pathway and the gene length ratio property to predict operons. Experimental results show that the prediction accuracy of this method reached 92.1%, 93.3% and 95.9% on the Bacillus subtilis genome, the Pseudomonas aeruginosa PA01 genome and the Staphylococcus aureus genome, respectively. This method has enabled us to predict operons with high accuracy for these three genomes, for which only limited data on the properties of the operon structure exists.

PPO: predictor for prokaryotic operons.

SUMMARY: We present an operon predictor for prokaryotic operons (PPO), which can predict operons in the entire prokaryotic genome. The prediction algorithm used in PPO allows the user to select binary particle swarm optimization (BPSO), a genetic algorithm (GA) or some other methods introduced in the literature to predict operons. The operon predictor on our web server and the provided database are easy to access and use. The main features offered are: (i) selection of the prediction algorithm; (ii) adjustable parameter settings of the prediction algorithm; (iii) graphic visualization of results; (iv) integrated database queries; (v) listing of experimentally verified operons; and (vi) related tools. AVAILABILITY AND IMPLEMENTATION: PPO is freely available at http://bio.kuas.edu.tw/PPO/.

Receptor discordance and phenotype change in metastatic breast cancer.

BACKGROUND: changes may occur in tumor phenotype and receptor status during the progression of breast cancer. Discordance between primary and metastases has implications for further treatment and prognosis. METHODS: 185 patients confirmed breast cancer metastasis were retrospectively analyzed during 1999-2019. All the pathological assessments of receptors and phenotypes of both primaries and metastases were recorded. RESULTS: rates of receptor discordance were 18.65%, 30.57%, and 16.06% for ER, PR, and HER2, respectively and 31.62% for phenotype change. Patients with ER discordance experienced a worse OS and PMS, and those with ER loss had worse PMS compared with ER positive concordance. Patients with PR discordance experienced poorer OS and loss of PR positivity also had decreased OS and PMS when comparing with PR positive concordance. There was also significantly poorer PMS of hormon receptor (HR) discordance than HR positive concordance. In phenotype change, the luminal A type concordance group showed better PMS result. CONCLUSIONS: this study demonstrated that discordance in subtype and receptor status between primary and metastatic lesions ultimately affects the survival and has a potential impact on treatment options.

Transferrin Modified GSH Sensitive Hyaluronic Acid Derivative Micelle to Deliver HSP90 Inhibitors to Enhance the Therapeutic Efficacy of Brain Cancers.

Herein, GSH-sensitive hyaluronic acid-poly(lactic-co-glycolic acid) (HA-SS-PLGA) was synthesized. Surface modification of PLGA with hyaluronic acid produced a highly stable micelle at physiological pH while a micelle was destabilized at a higher GSH level. Fluorescence microscopy results showed that rhodamine-encapsulated micelle was taken up by brain cancer cells, while competitive inhibition was observed in the presence of free HA and free transferrin. In vitro cytotoxicity results revealed that transferrin-targeted nanoformulated AUY922 (TF-NP-AUY922) shows higher cytotoxicity than either free AUY922 or non-targeted AUY922-loaded micelles (NP-AUY922). In comparison to the control groups, free AUY922, TF-NP-AUY922 or NP-AUY922 treatment revealed the upregulation of HSP70, while the expression of HSP90 client proteins was simultaneously depleted. In addition, the treatment group induced caspase-dependent PARP cleavage and the upregulation of p53 expression, which plays a key role in apoptosis of brain cancer cells. In vivo and ex vivo biodistribution studies showed that cypate-loaded micelle was taken up and accumulated in the tumor regions. Furthermore, in vivo therapeutic efficacy studies revealed that the AUY922-loaded micelle significantly suppressed tumor growth in comparison to the free AUY922, or control groups using tumor-bearing NOD-SCID mice. Moreover, biochemical index and histological analysis revealed synthesized micelle does not show any significant cytotoxicity to the selected major organs. Overall, a synthesized micelle is the best carrier for AUY922 to enhance the therapeutic efficiency of brain cancer.

Hospice delivery models and survival differences in the terminally ill: a large cohort study.

OBJECTIVE: A common difficulty at the end of life (EOL) is to determine an appropriate service model, such as hospice share care (HSC), hospice inpatient care (HIC) and hospice home care (HHC). This study aimed to recommend the appropriate hospice delivery model based on the physical, psychosocial and spiritual needs of patients referred for hospice care. METHODS: This cohort study included patients who received only one kind of hospice delivery model between 2006 and 2020. Data were analysed with descriptive statistics, Fisher's exact test, non-parametric analysis of variance, Kaplan-Meier curves and Cox proportional hazards model that determined the patients' clinical characteristics for a hospice delivery model and overall survival. RESULTS: A total of 8874 hospice patients were recruited, of which 7076 (79.7%) were HSC patients, 918 (10.4%) were HIC patients and 880 (9.9%) were HHC patients. There were significant differences in the physical symptoms and demographic, psychosocial and spiritual factors among the three groups (p<0.001). The patients who received the HHC were less to have dyspnoea (18.5%) and dysphagia (28.7%). The HIC patients showed higher severity of symptoms and experienced greater psychosocial distress (73.2%). The HSC is appropriate for noncancer patients . Patients with cancer were associated with less dyspnoea (32.4%) and dysphagia (46.5%). Patients with lung cancer who received the HHC had better survival than those who received other types of hospice care (HR=0.75, 95% CI: 0.66 to 0.86, p<0.001). CONCLUSIONS: This study provides guidance regarding the appropriate hospice service model, based on individualised palliative needs, targeting improvement in EOL care.

Operon prediction using chaos embedded particle swarm optimization.

Operons contain valuable information for drug design and determining protein functions. Genes within an operon are co-transcribed to a single-strand mRNA and must be coregulated. The identification of operons is, thus, critical for a detailed understanding of the gene regulations. However, currently used experimental methods for operon detection are generally difficult to implement and time consuming. In this paper, we propose a chaotic binary particle swarm optimization (CBPSO) to predict operons in bacterial genomes. The intergenic distance, participation in the same metabolic pathway and the cluster of orthologous groups (COG) properties of the Escherichia coli genome are used to design a fitness function. Furthermore, the Bacillus subtilis, Pseudomonas aeruginosa PA01, Staphylococcus aureus and Mycobacterium tuberculosis genomes are tested and evaluated for accuracy, sensitivity, and specificity. The computational results indicate that the proposed method works effectively in terms of enhancing the performance of the operon prediction. The proposed method also achieved a good balance between sensitivity and specificity when compared to methods from the literature.

Features for computational operon prediction in prokaryotes.

Accurate prediction of operons can improve the functional annotation and application of genes within operons in prokaryotes. Here, we review several features: (i) intergenic distance, (ii) metabolic pathways, (iii) homologous genes, (iv) promoters and terminators, (v) gene order conservation, (vi) microarray, (vii) clusters of orthologous groups, (viii) gene length ratio, (ix) phylogenetic profiles, (x) operon length/size and (xi) STRING database scores, as well as some other features, which have been applied in recent operon prediction methods in prokaryotes in the literature. Based on a comparison of the prediction performances of these features, we conclude that other, as yet undiscovered features, or feature selection with a receiver operating characteristic analysis before algorithm processing can improve operon prediction in prokaryotes.