Distinctive gene expression patterns in human mammary epithelial cells and breast cancers

ATP6AP1 promotes cell proliferation and tamoxifen resistance in luminal breast cancer by inducing autophagy

Autophagy is a highly conserved cellular process essential for maintaining cellular homeostasis and influencing cancer development. Lysosomal acidification and autophagosome-lysosome fusion are two important steps of autophagy degradation that are tightly regulated. Although many key proteins that regulate these two events have been identified, the effector proteins that co-regulate both steps remain to be explored. ATP6AP1, an accessory subunit of V-ATPase, plays a critical role in the assembly and regulation of V-ATPase. However, the function of ATP6AP1 in autophagy remains unknown, and the role of ATP6AP1 in cancer is still poorly understood. In this study, we found that ATP6AP1 is overexpressed in luminal breast cancer tissues and promotes the proliferation and tamoxifen resistance of luminal breast cancer cells both in vitro and in vivo. We also observed that high ATP6AP1 expression correlates with poor overall patient survival. Our research further revealed that ATP6AP1 enhances tamoxifen resistance by activating autophagy. Mechanistically, ATP6AP1 promotes autophagy by regulating both lysosomal acidification and autophagosome-lysosome fusion. Remarkably, ATP6AP1 induces lysosomal acidification through the regulation of V-ATPase assembly and facilitates autophagosome-lysosome fusion by enhancing the interaction between Rab7 and the HOPS complex. Together, our studies identify ATP6AP1 as a crucial regulator of autophagy, potentially serving as a valuable prognostic marker or therapeutic target in human luminal breast cancer.

A new insight into the impact of copy number variations on cell cycle deregulation of luminal-type breast cancer

Breast cancer is the most prevalent neoplasm in women. ER+ (Luminal subtype), representing over 70% of breast tumors, is a genetically diverse group. Structural and Numerical-Chromosomal instability initiates tumor development and is recognized as the primary driver of genetic alteration in luminal breast tumors. Genomic instability refers to the increased tendency of cancer cells to accumulate genomic alterations during cell proliferation. The cell cycle check-point response to constant and stable genomic alterations in tumor cells drives this process. The impact of CNV patterns and aneuploidies in cell cycle and proliferation perturbation has recently been highlighted by scientists in Luminal breast tumors. The impact of chromosomal instability on cancer therapy and prognosis is not a new concept. Still, the degree of emerging genomic instability leads to prognosis alteration following cell cycle deregulation by chromosomal instability could be predicted by CNVs-based reclassification of breast tumors. In this review, we try to explain the effect of CIN in the cell cycle that ended with genomic instability and altered prognosis and the impact of CIN in decision-making for a therapy strategy for patients with luminal breast cancer.

Clinical Implications of Breast Cancer Intrinsic Subtypes

Estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) breast cancers have different genomic architecture and show large-scale gene expression differences consistent with different cellular origins, which is reflected in the luminal (i.e., ER+) versus basal-like (i.e., ER-) molecular class nomenclature. These two major molecular subtypes have distinct epidemiological risk factors and different clinical behaviors. Luminal cancers can be subdivided further based on proliferative activity and ER signaling. Those with a high expression of proliferation-related genes and a low expression of ER-associated genes, called luminal B, have a high risk of early recurrence (i.e., within 5 years), derive significant benefit from adjuvant chemotherapy, and may benefit from adding immunotherapy to chemotherapy. This subset of luminal cancers is identified as the genomic high-risk ER+ cancers by the MammaPrint, Oncotype DX Recurrence Score, EndoPredict, Prosigna, and several other molecular prognostic assays. Luminal A cancers are characterized by low proliferation and high ER-related gene expression. They tend to have excellent prognosis with adjuvant endocrine therapy. Adjuvant chemotherapy may not improve their outcome further. These cancers correspond to the genomic low-risk categories. However, these cancers remain at risk for distant recurrence for extended periods of time, and over 50% of distant recurrences occur after 5 years. Basal-like cancers are uniformly highly proliferative and tend to recur within 3-5 years of diagnosis. In the absence of therapy, basal-like breast cancers have the worst survival, but these also include many highly chemotherapy-sensitive cancers. Basal-like cancers are often treated with preoperative chemotherapy combined with an immune checkpoint inhibitor which results in 60-65% pathologic complete response rates that herald excellent long-term survival. Patients with residual cancer after neoadjuvant therapy can receive additional postoperative chemotherapy that improves their survival. Currently, there is no clinically actionable molecular subclassification for basal-like cancers, although cancers with high androgen receptor (AR)-related gene expression and those with high levels of immune infiltration have better prognosis, but currently their treatment is not different from basal-like cancers in general. A clinically important, minor subset of breast cancers are characterized by frequent HER2 gene amplification and high expression of a few dozen genes, many residing on the HER2 amplicon. This is an important subset because of the highly effective HER2 targeted therapies which are synergistic with endocrine therapy and chemotherapy. The clinical behavior of HER2-enriched cancers is dominated by the underlying ER subtype. ER+/HER2-enriched cancers tend to have more indolent course and lesser chemotherapy sensitivity than their ER counterparts.

Diabetes and obesity: leveraging heterogeneity for precision medicine

The increasing prevalence of diabetes, obesity, and their cardiometabolic sequelae present major global health challenges and highlight shortfalls of current approaches to the prevention and treatment of these conditions. Representing the largest global burden of morbidity and mortality, the pathobiological processes underlying cardiometabolic diseases are in principle preventable and, even when disease is manifest, sometimes reversable. Nevertheless, with current clinical and public health strategies, goals of widespread prevention and remission remain largely aspirational. Application of precision medicine approaches that reduce errors and improve accuracy in medical and health recommendations has potential to accelerate progress towards these goals. Precision medicine must also maintain safety and ideally be cost-effective, as well as being compatible with an individual's preferences, capabilities, and needs. Initial progress in precision medicine was made in the context of rare diseases, with much focus on pharmacogenetic studies, owing to the cause of these diseases often being attributable to highly penetrant single gene mutations. By contrast, most obesity and type 2 diabetes are heterogeneous in aetiology and clinical presentation, underpinned by complex interactions between genetic and non-genetic factors. The heterogeneity of these conditions can be leveraged for development of approaches for precision therapies. Adequate characterization of the heterogeneity in cardiometabolic disease necessitates diversity of and synthesis across data types and research methods, ideally culminating in precision trials and real-world application of precision medicine approaches. This State-of-the-Art Review provides an overview of the current state of the science of precision medicine, as well as outlining a roadmap for study designs that maximise opportunities and address challenges to clinical implementation of precision medicine approaches in obesity and diabetes.

Discovery of Dual CDK6/BRD4 Inhibitor Inducing Apoptosis and Increasing the Sensitivity of Ferroptosis in Triple-Negative Breast Cancer

Bromodomain-containing protein 4 (BRD4) is the most promising target for the treatment of triple-negative breast cancer (TNBC). However, its inherent resistant and acquired drug resistance limits its potential clinical application. Recently it has been shown that cyclin-dependent kinases 4/6 (CDK4/6) inhibitors can reincrease the sensitivity of TNBC cells to BRD4 inhibitors by combination therapy, so we designed a series of dual target CDK6/BRD4 inhibitors. Among the newly synthesized compounds, BC13 exhibited potent inhibitory activity against CDK6 and BRD4. It also displayed potent antiproliferative activity against TNBC cells. In vivo experiments showed that BC13 has potent antitumor activity in the MDA-MB-231 xenograft mouse model, without observable side effects. BC13 demonstrates profound synergistic antitumor effects with ferroptosis inducer in TNBC cells. Therefore, BC13 is a novel dual inhibitor of CDK6/BRD4 for the treatment of TNBC either as a single agent or in combination with RSL3.

A related convolutional neural network for cancer diagnosis using microRNA data classification

This paper develops a method for cancer classification from microRNA data using a convolutional neural network (CNN)-based model optimized by genetic algorithm. The convolutional neural network has performed well in various recognition and perception tasks. This paper contributes to the cancer classification using a union of two CNNs. The method's performance is boosted by the relationship between CNNs and exchanging knowledge between them. Besides, communication between small sizes of CNNs reduces the need for large size CNNs and, consequently, the computational time and memory usage while preserving high accuracy. The method proposed is tested on microRNA dataset containing the genomic information of 8129 patients for 29 different types of cancer with 1046 gene expression. The classification accuracy of the selected genes obtained by the proposed approach is compared with the accuracy of 22 well-known classifiers on a real-world dataset. The classification accuracy of each cancer type is also ranked with the results of 77 classifiers reported in previous works. The proposed approach shows accuracy of 100% in 24 out of 29 classes and in seven cases out of 29, the method achieved 100% accuracy that no classifier in other studies has reached. Performance analysis is performed using performance metrics.

The curious case of type I interferon signaling in cancer

Cytokines are the crucial signaling proteins that mediate the crosstalks between the cells of tumor microenvironment (TME). Interferon-1 (IFN-1) are the important cytokines that are widely known for their tumor suppressive roles comprising of cancer cell intrinsic and extrinsic mechanisms. Despite having known antitumor effects, IFN-1 are also reported to have tumor promoting functions under varying circumstances. This dichotomy in the functions of IFN-1 is largely attributed to the acute and chronic activation of IFN-1 signaling in TME. The chronic activation of IFN-1 signaling in tumor cells results in altered stimulation of downstream pathways that result in the expression of tumor promoting proteins, while the acute IFN-1 signaling activation maintains its tumor inhibiting functions. In the present review, we have discussed the anti- and pro-tumor actions of IFN-1 signaling under acute and chronic IFN-1 signaling activation. We have also discussed the downstream changes in signaling components that result in tumor supportive functions of a constitutive IFN-1 signaling. We have further discussed the possible strategies to overcome the detrimental effects of chronic IFN-1 pathway activation and to successfully employ IFN-1 for their beneficial anti-tumor effects.

Cell-cycle phase progression analysis identifies three unique phenotypes in soft tissue sarcoma

PURPOSE

Loddo et al. (Br J Cancer 100:959-70, 2009) established the prognostic significance of cell cycle markers and "Cell-Cycle Phenotypes" in breast carcinoma. This study aims to 1) identify prognostic cell-cycle markers in sarcoma, and 2) assess the prognostic potential of specific cell-cycle phenotypes in sarcoma.

METHODS

Tissue samples from 128 soft tissue sarcomas were stained for four cell cycle-specific markers: Mcm2, Geminin, Plk1, and H3S10ph. Only primary soft tissue tumors (liposarcoma, leiomyosarcoma, synovial sarcoma, and undifferentiated pleomorphic sarcoma) were included in the analysis. Any tumor coming from a recurrent or metastatic lesion were excluded from the analysis. Three cell-cycle phenotypes (I, II, III) were derived from marker expression patterns. Prognostic significance was evaluated in a subset of primary soft tissue sarcomas using Cox regression for survival analysis.

RESULTS

Compared to phenotype I, the phenotype III tumors had a decreased 5-year overall survival (HR 6.81 [2.36-19.61]; p =  < 0.001), 5-year disease-free survival (HR 1.07 (1.02-1.18); p = 0.004), and 5-year metastasis-free survival (HR 4.34 [1.58-11.93]; p = 0.004). High expression of Plk1 was associated with decreased 5-year overall survival (HR: 4.04 CI [1.21-6.67; p = 0.02) and 5-year metastasis-free survival (HR: 2.91 CI [1.15-7.37]; p = 0.03). Geminin was also found to have a decreased 5-year overall survival (HR:2.84 CI [1.21-6.67]; p = 0.02). No statistical difference in prognostication were noted between phenotypes and the AJCC system.

CONCLUSIONS

We identified three unique sarcoma cell cycle phenotypes that have prognostic significance. This performs similarly to the AJCC staging system.

Intracellular pH differentially regulates transcription of metabolic and signaling pathways in normal epithelial cells

Intracellular pH (pHi) dynamics regulate normal cell function, and dysregulated pHi dynamics is an emerging hallmark of cancer (constitutively increased pHi) and neurodegeneration (constitutively decreased pHi). However, the molecular mechanisms by which pHi dynamics regulate cell biology are poorly understood. Here, we discovered that altering pHi in normal human breast epithelial cells triggers global transcriptional changes. We identified 176 genes differentially regulated by pHi, with pHi-dependent genes clustering in signaling and glycolytic pathways. Using various normal epithelial cell models, we showed pH-dependent Notch homolog 1 protein expression, with increased protein abundance at high pHi. This resulted in pH-dependent downstream signaling, with increased Notch homolog 1 signaling at high pHi. We also found that high pHi increased the expression of glycolytic enzymes and regulators of pyruvate fate, including lactate dehydrogenase and pyruvate dehydrogenase kinase. These transcriptional changes were sufficient to alter lactate production, with high pHi shifting these normal epithelial cells toward a glycolytic metabolism and increasing lactate production. Thus, pHi dynamics transcriptionally regulate signaling and metabolic pathways in normal epithelial cells. Our data reveal new molecular regulators of pHi-dependent biology and a role for increased pHi in driving the acquisition of cancer-associated signaling and metabolic changes in normal human epithelial cells.

Combination of US hyperthermia and radiotherapy on a preclinical glioblastoma model

In this work the effect of combining ultrasound (US) hyperthermia (HT) with radiotherapy (RT) was investigated. The treatment was applied to a GBM xenograft nude mouse model obtained by injecting 2 × 10 6 U87 luc+ cells. The combined treatment group received 6 Gy and HT at 43 ∘ for 8 min. The ultrasound field was generated by a closed-loop computationally controlled system, consisting of a High Intensity Focused Ultrasound (HIFU) transducer with centre frequency 3.57 MHz, a power amplifier, a function generator and a MATLAB controller. A mechanical cone adaptor has been designed to use the HIFU beam at a pre-defined post-focal distance. Two thermocouples were placed between the mechanical cone and the mice skin to measure and control the temperature during the HT treatment. Radiotherapy was carried out by using a dedicated small animal image guided radiotherapy system. Measurements of tumor volume performed with a caliper showed good tumor control for the RT-HT group with respect to the RT or control groups for up to 21 days after treatment. The mean value of the normalized (before therapy) tumor volume was almost equal to 0.5 for two weeks after treatment with an increase to 1.5 at sacrifice. The control and HT groups showed a higher value of about 1.5 during the first two weeks and 3.5 at the end of the follow-up period. We concluded that the use of HT as a radiosensitizer can improve the outcome for glioblastoma treatments.

A Novel Cytotoxic Mechanism for Triple-Negative Breast Cancer Cells Induced by the Type II Heat-Labile Enterotoxin LT-IIc through Ganglioside Ligation

Triple-negative breast cancer (TNBC), which constitutes 10-20 percent of all breast cancers, is aggressive, has high metastatic potential, and carries a poor prognosis due to limited treatment options. LT-IIc, a member of the type II subfamily of ADP-ribosylating-heat-labile enterotoxins that bind to a distinctive set of cell-surface ganglioside receptors-is cytotoxic toward TNBC cell lines, but has no cytotoxic activity for non-transformed breast epithelial cells. Here, primary TNBC cells, isolated from resected human tumors, showed an enhanced cytotoxic response specifically toward LT-IIc, in contrast to other enterotoxins that were tested. MDA-MB-231 cells, a model for TNBC, were used to evaluate potential mechanisms of cytotoxicity by LT-IIc, which induced elevated intracellular cAMP and stimulated the cAMP response element-binding protein (CREB) signaling pathway. To dissect the role of ADP-ribosylation, cAMP induction, and ganglioside ligation in the cytotoxic response, MDA-MB-231 cells were exposed to wild-type LT-IIc, the recombinant B-pentamer of LT-IIc that lacks the ADP-ribosylating A polypeptide, or mutants of LT-IIc with an enzymatically inactivated A1-domain. These experiments revealed that the ADP-ribosyltransferase activity of LT-IIc was nonessential for inducing the lethality of MDA-MB-231 cells. In contrast, a mutant LT-IIc with an altered ganglioside binding activity failed to trigger a cytotoxic response in MDA-MB-231 cells. Furthermore, the pharmacological inhibition of ganglioside expression protected MDA-MB-231 cells from the cytotoxic effects of LT-IIc. These data establish that ganglioside ligation, but not the induction of cAMP production nor ADP-ribosyltransferase activity, is essential to initiating the LT-IIc-dependent cell death of MDA-MB-231 cells. These experiments unveiled previously unknown properties of LT-IIc and gangliosides in signal transduction, offering the potential for the targeted treatment of TNBC, an option that is desperately needed.

Themis: advancing precision oncology through comprehensive molecular subtyping and optimization

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

A CARM1 Inhibitor Potently Suppresses Breast Cancer Both In Vitro and In Vivo

CARM1, belonging to the protein arginine methyltransferase (PRMT) family, is intricately associated with the progression of cancer and is viewed as a promising target for both cancer diagnosis and therapy. However, the number of specific and potent CARM1 inhibitors is limited. We herein discovered a CARM1 inhibitor, iCARM1, that showed better specificity and activity toward CARM1 compared to the known CARM1 inhibitors, EZM2302 and TP-064. Similar to CARM1 knockdown, iCARM1 suppressed the expression of oncogenic estrogen/ERα-target genes, whereas activated type I interferon (IFN) and IFN-induced genes (ISGs) in breast cancer cells. Consequently, iCARM1 potently suppressed breast cancer cell growth both in vitro and in vivo. The combination of iCARM1 with either endocrine therapy drugs or etoposide demonstrated synergistic effects in inhibiting the growth of breast tumors. In summary, targeting CARM1 by iCARM1 effectively suppresses breast tumor growth, offering a promising therapeutic approach for managing breast cancers in clinical settings.

Predicting transcription factor activity using prior biological information

Dysregulation of normal transcription factor activity is a common driver of disease. Therefore, the detection of aberrant transcription factor activity is important to understand disease pathogenesis. We have developed Priori, a method to predict transcription factor activity from RNA sequencing data. Priori has two key advantages over existing methods. First, Priori utilizes literature-supported regulatory information to identify transcription factor-target gene relationships. It then applies linear models to determine the impact of transcription factor regulation on the expression of its target genes. Second, results from a third-party benchmarking pipeline reveals that Priori detects aberrant activity from 124 single-gene perturbation experiments with higher sensitivity and specificity than 11 other methods. We applied Priori and other top-performing methods to predict transcription factor activity from two large primary patient datasets. Our work demonstrates that Priori uniquely discovered significant determinants of survival in breast cancer and identified mediators of drug response in leukemia.

Lifetime alcohol consumption patterns and young-onset breast cancer by subtype among Non-Hispanic Black and White women in the Young Women's Health History Study

PURPOSE

The role of alcohol in young-onset breast cancer (YOBC) is unclear. We examined associations between lifetime alcohol consumption and YOBC in the Young Women's Health History Study, a population-based case-control study of breast cancer among Non-Hispanic Black and White women < 50 years of age.

METHODS

Breast cancer cases (n = 1,812) were diagnosed in the Metropolitan Detroit and Los Angeles County SEER registry areas, 2010-2015. Controls (n = 1,381) were identified through area-based sampling and were frequency-matched to cases by age, site, and race. Alcohol consumption and covariates were collected from in-person interviews. Weighted multivariable logistic regression was conducted to calculate adjusted odds ratios (aOR) and 95% confidence intervals (CI) for associations between alcohol consumption and YOBC overall and by subtype (Luminal A, Luminal B, HER2, or triple negative).

RESULTS

Lifetime alcohol consumption was not associated with YOBC overall or with subtypes (all ptrend ≥ 0.13). Similarly, alcohol consumption in adolescence, young and middle adulthood was not associated with YOBC (all ptrend ≥ 0.09). An inverse association with triple-negative YOBC, however, was observed for younger age at alcohol use initiation (< 18 years vs. no consumption), aOR (95% CI) = 0.62 (0.42, 0.93). No evidence of statistical interaction by race or household poverty was observed.

CONCLUSIONS

Our findings suggest alcohol consumption has a different association with YOBC than postmenopausal breast cancer-lifetime consumption was not linked to increased risk and younger age at alcohol use initiation was associated with a decreased risk of triple-negative YOBC. Future studies on alcohol consumption in YOBC subtypes are warranted.

Machine learning-based models for the prediction of breast cancer recurrence risk

Breast cancer is the most common malignancy diagnosed in women worldwide. The prevalence and incidence of breast cancer is increasing every year; therefore, early diagnosis along with suitable relapse detection is an important strategy for prognosis improvement. This study aimed to compare different machine algorithms to select the best model for predicting breast cancer recurrence. The prediction model was developed by using eleven different machine learning (ML) algorithms, including logistic regression (LR), random forest (RF), support vector classification (SVC), extreme gradient boosting (XGBoost), gradient boosting decision tree (GBDT), decision tree, multilayer perceptron (MLP), linear discriminant analysis (LDA), adaptive boosting (AdaBoost), Gaussian naive Bayes (GaussianNB), and light gradient boosting machine (LightGBM), to predict breast cancer recurrence. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and F1 score were used to evaluate the performance of the prognostic model. Based on performance, the optimal ML was selected, and feature importance was ranked by Shapley Additive Explanation (SHAP) values. Compared to the other 10 algorithms, the results showed that the AdaBoost algorithm had the best prediction performance for successfully predicting breast cancer recurrence and was adopted in the establishment of the prediction model. Moreover, CA125, CEA, Fbg, and tumor diameter were found to be the most important features in our dataset to predict breast cancer recurrence. More importantly, our study is the first to use the SHAP method to improve the interpretability of clinicians to predict the recurrence model of breast cancer based on the AdaBoost algorithm. The AdaBoost algorithm offers a clinical decision support model and successfully identifies the recurrence of breast cancer.

The clinical relevance of OSM in inflammatory diseases: a comprehensive review

Oncostatin M (OSM) is a pleiotropic cytokine involved in a variety of inflammatory responses such as wound healing, liver regeneration, and bone remodeling. As a member of the interleukin-6 (IL-6) family of cytokines, OSM binds the shared receptor gp130, recruits either OSMRβ or LIFRβ, and activates a variety of signaling pathways including the JAK/STAT, MAPK, JNK, and PI3K/AKT pathways. Since its discovery in 1986, OSM has been identified as a significant contributor to a multitude of inflammatory diseases, including arthritis, inflammatory bowel disease, lung and skin disease, cardiovascular disease, and most recently, COVID-19. Additionally, OSM has also been extensively studied in the context of several cancer types including breast, cervical, ovarian, testicular, colon and gastrointestinal, brain,lung, skin, as well as other cancers. While OSM has been recognized as a significant contributor for each of these diseases, and studies have shown OSM inhibition is effective at treating or reducing symptoms, very few therapeutics have succeeded into clinical trials, and none have yet been approved by the FDA for treatment. In this review, we outline the role OSM plays in a variety of inflammatory diseases, including cancer, and outline the previous and current strategies for developing an inhibitor for OSM signaling.

THE SCALABLE BIRTH-DEATH MCMC ALGORITHM FOR MIXED GRAPHICAL MODEL LEARNING WITH APPLICATION TO GENOMIC DATA INTEGRATION

Recent advances in biological research have seen the emergence of high-throughput technologies with numerous applications that allow the study of biological mechanisms at an unprecedented depth and scale. A large amount of genomic data is now distributed through consortia like The Cancer Genome Atlas (TCGA), where specific types of biological information on specific type of tissue or cell are available. In cancer research, the challenge is now to perform integrative analyses of high-dimensional multi-omic data with the goal to better understand genomic processes that correlate with cancer outcomes, e.g. elucidate gene networks that discriminate a specific cancer subgroups (cancer sub-typing) or discovering gene networks that overlap across different cancer types (pan-cancer studies). In this paper, we propose a novel mixed graphical model approach to analyze multi-omic data of different types (continuous, discrete and count) and perform model selection by extending the Birth-Death MCMC (BDMCMC) algorithm initially proposed by Stephens (2000) and later developed by Mohammadi and Wit (2015). We compare the performance of our method to the LASSO method and the standard BDMCMC method using simulations and find that our method is superior in terms of both computational efficiency and the accuracy of the model selection results. Finally, an application to the TCGA breast cancer data shows that integrating genomic information at different levels (mutation and expression data) leads to better subtyping of breast cancers.

The Story of the Magee Equations: The Ultimate in Applied Immunohistochemistry

Magee equations (MEs) are a set of multivariable models that were developed to estimate the actual Onco type DX (ODX) recurrence score in invasive breast cancer. The equations were derived from standard histopathologic factors and semiquantitative immunohistochemical scores of routinely used biomarkers. The 3 equations use slightly different parameters but provide similar results. ME1 uses Nottingham score, tumor size, and semiquantitative results for estrogen receptor (ER), progesterone receptor, HER2, and Ki-67. ME2 is similar to ME1 but does not require Ki-67. ME3 includes only semiquantitative immunohistochemical expression levels for ER, progesterone receptor, HER2, and Ki-67. Several studies have validated the clinical usefulness of MEs in routine clinical practice. The new cut-off for ODX recurrence score, as reported in the Trial Assigning IndividuaLized Options for Treatment trial, necessitated the development of Magee Decision Algorithm (MDA). MEs, along with mitotic activity score can now be used algorithmically to safely forgo ODX testing. MDA can be used to triage cases for molecular testing and has the potential to save an estimated $300,000 per 100 clinical requests. Another potential use of MEs is in the neoadjuvant setting to appropriately select patients for chemotherapy. Both single and multi-institutional studies have shown that the rate of pathologic complete response (pCR) to neoadjuvant chemotherapy in ER+/HER2-negative patients can be predicted by ME3 scores. The estimated pCR rates are 0%, <5%, 14%, and 35 to 40% for ME3 score <18, 18 to 25, >25 to <31, and 31 or higher, respectively. This information is similar to or better than currently available molecular tests. MEs and MDA provide valuable information in a time-efficient manner and are available free of cost for anyone to use. The latter is certainly important for institutions in resource-poor settings but is also valuable for large institutions and integrated health systems.

Multiparametric MRI radiomics in prostate cancer for predicting Ki-67 expression and Gleason score: a multicenter retrospective study

PURPOSE

Prostate cancer (PCa) with high Ki-67 expression and high Gleason Scores (GS) tends to have aggressive clinicopathological characteristics and a dismal prognosis. In order to predict the Ki-67 expression status and the GS in PCa, we sought to construct and verify MRI-based radiomics signatures.

METHODS AND MATERIALS

We collected T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) images from 170 PCa patients at three institutions and extracted 321 original radiomic features from each image modality. We used support vector machine (SVM) and least absolute shrinkage and selection operator (LASSO) logistic regression to select the most informative radiomic features and built predictive models using up sampling and feature selection techniques. Using receiver operating characteristic (ROC) analysis, the discriminating power of this feature was determined. Subsequent decision curve analysis (DCA) assessed the clinical utility of the radiomic features. The Kaplan-Meier (KM) test revealed that the radiomics-predicted Ki-67 expression status and GS were prognostic factors for PCa survival.

RESULT

The hypothesized radiomics signature, which included 15 and 9 selected radiomics features, respectively, was significantly correlated with pathological Ki-67 and GS outcomes in both the training and validation datasets. Areas under the curve (AUC) for the developed model were 0.813 (95% CI 0.681,0.930) and 0.793 (95% CI 0.621, 0.929) for the training and validation datasets, respectively, demonstrating discrimination and calibration performance. The model's clinical usefulness was verified using DCA. In both the training and validation sets, high Ki-67 expression and high GS predicted by radiomics using SVM models were substantially linked with poor overall survival (OS).

CONCLUSIONS

Both Ki-67 expression status and high GS correlate with PCa patient survival outcomes; therefore, the ability of the SVM classifier-based model to estimate Ki-67 expression status and the Lasso classifier-based model to assess high GS may enhance clinical decision-making.

Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.

Molecular Characterization and Landscape of Breast cancer Models from a multi-omics Perspective

Breast cancer is well-known to be a highly heterogenous disease. This facet of cancer makes finding a research model that mirrors the disparate intrinsic features challenging. With advances in multi-omics technologies, establishing parallels between the various models and human tumors is increasingly intricate. Here we review the various model systems and their relation to primary breast tumors using available omics data platforms. Among the research models reviewed here, breast cancer cell lines have the least resemblance to human tumors since they have accumulated many mutations and copy number alterations during their long use. Moreover, individual proteomic and metabolomic profiles do not overlap with the molecular landscape of breast cancer. Interestingly, omics analysis revealed that the initial subtype classification of some breast cancer cell lines was inappropriate. In cell lines the major subtypes are all well represented and share some features with primary tumors. In contrast, patient-derived xenografts (PDX) and patient-derived organoids (PDO) are superior in mirroring human breast cancers at many levels, making them suitable models for drug screening and molecular analysis. While patient derived organoids are spread across luminal, basal- and normal-like subtypes, the PDX samples were initially largely basal but other subtypes have been increasingly described. Murine models offer heterogenous tumor landscapes, inter and intra-model heterogeneity, and give rise to tumors of different phenotypes and histology. Murine models have a reduced mutational burden compared to human breast cancer but share some transcriptomic resemblance, and representation of many breast cancer subtypes can be found among the variety subtypes. To date, while mammospheres and three- dimensional cultures lack comprehensive omics data, these are excellent models for the study of stem cells, cell fate decision and differentiation, and have also been used for drug screening. Therefore, this review explores the molecular landscapes and characterization of breast cancer research models by comparing recent published multi-omics data and analysis.

Polysaccharides and Structural Proteins as Components in Three-Dimensional Scaffolds for Breast Cancer Tissue Models: A Review

Breast cancer is the most common cancer among women, and even though treatments are available, efficiency varies with the patients. In vitro 2D models are commonly used to develop new treatments. However, 2D models overestimate drug efficiency, which increases the failure rate in later phase III clinical trials. New model systems that allow extensive and efficient drug screening are thus required. Three-dimensional printed hydrogels containing active components for cancer cell growth are interesting candidates for the preparation of next generation cancer cell models. Macromolecules, obtained from marine- and land-based resources, can form biopolymers (polysaccharides such as alginate, chitosan, hyaluronic acid, and cellulose) and bioactive components (structural proteins such as collagen, gelatin, and silk fibroin) in hydrogels with adequate physical properties in terms of porosity, rheology, and mechanical strength. Hence, in this study attention is given to biofabrication methods and to the modification with biological macromolecules to become bioactive and, thus, optimize 3D printed structures that better mimic the cancer cell microenvironment. Ink formulations combining polysaccharides for tuning the mechanical properties and bioactive polymers for controlling cell adhesion is key to optimizing the growth of the cancer cells.

Haloarchaeal carotenoids exert an in vitro antiproliferative effect on human breast cancer cell lines

Oxidative stress has been linked to the onset and progression of different neoplasia. Antioxidants might help prevent it by modulating biochemical processes involved in cell proliferation. Here, the aim was to evaluate the in vitro cytotoxic effect of Haloferax mediterranei bacterioruberin-rich carotenoid extracts (BRCE) (0-100 µg/ml) in six BC cell lines, representative of the intrinsic phenotypes and a healthy mammary epithelium cell line. Cell index values were obtained using xCELLigence RTCA System. Furthermore, cell diameter, viability, and concentration were measured at 12 h, 24 h, and 30 h. We found that BC cells were selectively affected by BRCE (SI > 1, p < 0.005). After 30 h, the population of BC cells exposed to 100 µg/ml was 11.7-64.6% of the control (p = 0.0001-0.0009). Triple-negative cells were significantly affected [MDA-MB-231 (IC₅₀ 51.8 µg/ml, p < 0.0001) and MDA-MB-468 (IC₅₀ 63.9 µg/ml, p < 0.0001)]. Cell size was also reduced after 30 h treatment in 3.8 (± 0.1) µm and 3.3 (± 0.02) µm for SK-BR-3 (p < 0.0001) and MDA-MB-468 (p < 0.0001), respectively. In conclusion, Hfx. mediterranei BRCE exerts a cytotoxic effect on BC cell lines representative of all studied intrinsic subtypes. Furthermore, results obtained for MDA-MB-231 and MDA-MB-468 are very promising, considering the aggressive behaviour of the triple-negative BC subtype.

Tumor heterogeneity: An oncogenic driver of PDAC progression and therapy resistance under stress conditions

Pancreatic ductal adenocarcinoma (PDAC) is a clinically challenging disease usually diagnosed at advanced or metastasized stage. By this year end, there are an expected increase in 62,210 new cases and 49,830 deaths in the United States, with 90% corresponding to PDAC subtype alone. Despite advances in cancer therapy, one of the major challenges combating PDAC remains tumor heterogeneity between PDAC patients and within the primary and metastatic lesions of the same patient. This review describes the PDAC subtypes based on the genomic, transcriptional, epigenetic, and metabolic signatures observed among patients and within individual tumors. Recent studies in tumor biology suggest PDAC heterogeneity as a major driver of disease progression under conditions of stress including hypoxia and nutrient deprivation, leading to metabolic reprogramming. We therefore advance our understanding in identifying the underlying mechanisms that interfere with the crosstalk between the extracellular matrix components and tumor cells that define the mechanics of tumor growth and metastasis. The bilateral interaction between the heterogeneous tumor microenvironment and PDAC cells serves as another important contributor that characterizes the tumor-promoting or tumor-suppressing phenotypes providing an opportunity for an effective treatment regime. Furthermore, we highlight the dynamic reciprocating interplay between the stromal and immune cells that impact immune surveillance or immune evasion response and contribute towards a complex process of tumorigenesis. In summary, the review encapsulates the existing knowledge of the currently applied treatments for PDAC with emphasis on tumor heterogeneity, manifesting at multiple levels, impacting disease progression and therapy resistance under stress.

Stable Isotope Tracing Reveals an Altered Fate of Glucose in N-Acetyltransferase 1 Knockout Breast Cancer Cells

Breast cancer is one of the leading causes of cancer death. Recent studies found that arylamine N-acetyltransferase 1 (NAT1) is frequently upregulated in breast cancer, further suggesting NAT1 could be a potential therapeutic target for breast cancer. Previous publications have established that NAT1 knockout (KO) in breast cancer cell lines leads to growth reduction both in vitro and in vivo and metabolic changes. These reports suggest that NAT1 contributes to the energy metabolism of breast cancer cells. Proteomic analysis and non-targeted metabolomics suggested that NAT1 KO may change the fate of glucose as it relates to the TCA/KREB cycle of the mitochondria of breast cancer cells. In this current study, we used [U-13C]-glucose stable isotope resolved metabolomics to determine the effect of NAT1 KO on the metabolic profile of MDA-MB-231 breast cancer cells. We incubated breast cancer cells (MDA-MB-231 cells) and NAT1 Crispr KO cells (KO#2 and KO#5) with [U-13C]-glucose for 24 h. Tracer incubation polar metabolites from the cells were extracted and analyzed by 2DLC-MS, and metabolite differences were compared between the parental and NAT1 KO cells. Differences consistent between the two KO cells were considered changes due to the loss of NAT1. The data revealed decreases in the 13C enrichment of TCA/Krebs cycle intermediates in NAT1 KO cells compared to the MDA-MB-231 cells. Specifically, 13C-labeled citrate, isocitrate, a-ketoglutarate, fumarate, and malate were all decreased in NAT1 KO cells. We also detected increased 13C-labeled L-lactate levels in the NAT1 KO cells and decreased 13C enrichment in some nucleotides. Pathway analysis showed that arginine biosynthesis, alanine, aspartate and glutamate metabolism, and the TCA cycle were most affected. These data provide additional evidence supporting the impacts of NAT1 knockout on cellular energy metabolism. The data suggest that NAT1 expression is important for the proper functioning of mitochondria and the flux of glucose through the TCA/Krebs cycle in breast cancer cells. The metabolism changes in the fate of glucose in NAT1 KO breast cancer cells offer more insight into the role of NAT1 in energy metabolism and the growth of breast cancer cells. These data provide additional evidence that NAT1 may be a useful therapeutic target for breast cancer.

Clinical correlation analysis of HPV infection in adult laryngeal papilloma and adverse events

OBJECT

To explore the factors affecting dysplasia and carcinogenesis in adult patients with laryngeal papilloma, and the clinical differences between human papillomavirus (HPV)-positive and HPV-negative patients.

METHODS

Clinical data of 80 adult patients with laryngeal papilloma and associated adverse events were collected retrospectively. They had undergone surgery in the Department of Otolaryngology Head and Neck, Beijing Tongren Hospital, Capital Medical University between January 2010 and December 2020. HPV infection was detected using RNA in situ hybridization.

RESULTS

Regression analysis showed that multiple lesions and high Ki-67 expression were independent factors affecting the occurrence of adverse events. Differences between the HPV-positive and HPV-negative groups were compared. The age and Ki-67 expression in the HPV-negative group were significantly higher than those in the HPV-positive group. In the severe dysplasia to carcinogenesis subgroup, the proportion of HPV-negative patients was significantly higher than that in the mild to moderate dysplasia subgroup. There was a high correlation between positive p16 immunohistochemistry (IHC) and positive HPV.

CONCLUSIONS

Multiple lesions and high Ki-67 expression are independent factors that are linked with adverse laryngeal papilloma progression. Elderly HPV-negative patients are at an increased risk of severe dysplasia and carcinogenesis. Positive p16 IHC was very accurate in detecting HPV infection.

Novel Aggregation-Induced Emission Fluorescent Molecule for Platinum(IV) Ion-Selective Recognition and Imaging of Controlled Release in Cells

The loading, delivery, and release of Pt(IV) precursors in living organisms are important aspects of exploring the development of platinum drugs. In recent years, the biological application of the fluorescent sensors to platinum drugs has been insufficient to meet the study of Pt(IV) precursors. It is urgent to design and develop a biocompatible, multifunctional fluorescent sensor for the study of loading, transport, and release of Pt(IV) ions. Herein, we report a fluorescent molecule (E)-6-(diethylamino)-N'-(4-(diphenylamino) benzylidene)-2-oxo-2H-chromene-3 carbohydrazide (CHTPA). CHTPA has good sensitivity and selectivity to Pt(IV) when the water content is 5%, and significant increase of the fluorescence emission intensity of CHTPA is observed with Pt(IV) concentration. The sensing mechanism is attributed to photo-induced electron transfer, which is verified by X-ray absorption near edge spectroscopy spectra, UV-vis absorption spectroscopy, ¹H NMR spectra, and Fourier transform infrared spectra. Furthermore, the CHTPA-Pt(IV) complex is able to release Pt(IV) in aqueous solution, and the green fluorescence of CHTPA based on the aggregation-induced emission effect can be observed. Inspired by these, the amphiphilic block copolymer poly(ethyloxide)-block-polystyrene (PEO-b-PS) is used to prepare the nonconjugated polymer dots (Pdots). The experimental results show that Pdots can effectively slow down the release speed of Pt(IV) in aqueous solution and it has a great monodispersity in aqueous solution. Meanwhile, Pdots show low cytotoxicity, and this is favorable for intracellular applications. The investigation of cellular imaging indicates that these Pdots can act as a carrier to deliver Pt(IV) into MCF-7 cells for visualized delivery and sustained release of platinum(IV) ions. Therefore, this study provides a new avenue to design and develop a biocompatible multifunctional fluorescent sensor for studying the loading, delivery, and release of Pt(IV) in cells.

Degraded RNA from Human Anterior Cruciate Ligaments Yields Valid Gene Expression Profiles

Correlating gene expression patterns with biomechanical properties of connective tissues provides insights into the molecular processes underlying the tissue growth and repair. Cadaveric specimens such as human knees are widely considered suitable for biomechanical studies, but their usefulness for gene expression experiments is potentially limited by the unavoidable, nuclease-mediated degradation of RNA. Here, we tested whether valid gene expression profiles can be obtained using degraded RNA from human anterior cruciate ligaments (ACLs). Human ACL RNA (N = 6) degraded in vitro by limited ribonuclease digestion resemble highly degraded RNA isolated from cadaveric tissue. PCR threshold cycle (Ct) values for 90 transcripts (84 extracellular matrix, 6 housekeeping) in degraded RNAs variably ranged higher than values obtained from their corresponding non-degraded RNAs, reflecting both the expected loss of target templates in the degraded preparations as well as differences in the extent of degradation. Relative Ct values obtained for mRNAs in degraded preparations strongly correlated with the corresponding levels in non-degraded RNA, both for each ACL as well as for the pooled results from all six ACLs. Nuclease-mediated degradation produced similar, strongly correlated losses of housekeeping and non-housekeeping gene mRNAs. RNA degraded in situ yielded comparable results, confirming that in vitro digestion effectively modeled degradation by endogenous ribonucleases in frozen and thawed ACL. We conclude that, contrary to conventional wisdom, PCR-based expression analyses can yield valid mRNA profiles even from RNA preparations that are more than 90% degraded, such as those obtained from connective tissues subjected to biomechanical studies. Furthermore, legitimate quantitative comparisons between variably degraded tissues can be made by normalizing data to appropriate housekeeping transcripts.

The relationships of OSBPL3 expression with KI-67 expression and KRAS mutations in CRC: implications for diagnosis and prognosis

BACKGROUND

OSBPL3 is overexpressed in a variety of malignancies and is closely associated with tumor growth and metastasis. However, its expression and function in colorectal cancer (CRC) are unclear. We aimed to investigate its prognostic and therapeutic value in this disease by detecting its expression in CRC and its correlation with the clinicopathological characteristics and prognosis of patients.

METHODS

A total of 92 CRC samples were included in this study. According to the 2020 WHO diagnostic criteria, the criteria of the American Joint Committee on Cancer (AJCC) 8th edition staging system were used. OSBPL3 and Ki-67 expression in these samples was detected by immunohistochemistry. OSBPL3 mRNA expression was detected by qRT-PCR. KRAS/NRAS mutations were detected by an amplification refractory mutation system (ARMS). Data analysis was performed using the statistical analysis software Prism 8.

RESULTS

OSBPL3 was found to be significantly overexpressed in CRC tumor tissues and was associated with worse progression-free survival and overall survival in patients. Additionally, OSBPL3 expression was negatively correlated with the degree of tumor differentiation. KRAS mutations were detected in approximately 32.6% of patients and were significantly associated with high OSBPL3 expression. In addition, OSBPL3 and Ki-67 expression was significantly correlated.

CONCLUSIONS

OSBPL3 is highly expressed in CRC samples and predicts a worse prognosis. OSBPL3 may become a new potential therapeutic target for CRC.

Identifying the genes impacted by cell proliferation in proteomics and transcriptomics studies

Hypothesis-free high-throughput profiling allows relative quantification of thousands of proteins or transcripts across samples and thereby identification of differentially expressed genes. It is used in many biological contexts to characterize differences between cell lines and tissues, identify drug mode of action or drivers of drug resistance, among others. Changes in gene expression can also be due to confounding factors that were not accounted for in the experimental plan, such as change in cell proliferation. We combined the analysis of 1,076 and 1,040 cell lines in five proteomics and three transcriptomics data sets to identify 157 genes that correlate with cell proliferation rates. These include actors in DNA replication and mitosis, and genes periodically expressed during the cell cycle. This signature of cell proliferation is a valuable resource when analyzing high-throughput data showing changes in proliferation across conditions. We show how to use this resource to help in interpretation of in vitro drug screens and tumor samples. It informs on differences of cell proliferation rates between conditions where such information is not directly available. The signature genes also highlight which hits in a screen may be due to proliferation changes; this can either contribute to biological interpretation or help focus on experiment-specific regulation events otherwise buried in the statistical analysis.

Slow degrading Mg-based materials induce tumor cell dormancy on an osteosarcoma-fibroblast coculture model

Osteosarcoma is one of the most common cancers in young adults and is commonly treated using surgery and chemotherapy. During the past years, these therapy approaches improved but failed to ameliorate the outcomes. Therefore, novel, targeted therapeutic approaches should be established to enhance treatment success while preserving patient's quality of life. Recent studies suggest the application of degradable magnesium (Mg) alloys as orthopedic implants bearing a potential antitumor activity. Here, we examined the influence of Mg-based materials on an osteosarcoma-fibroblast coculture. Both, Mg and Mg-6Ag did not lead to tumor cell apoptosis at low degradation rates. Instead, the Mg-based materials induced cellular dormancy in the cancer cells indicated by a lower number of Ki-67 positive cancer cells and a higher p38 expression. This dormancy-like state could be reversed by reseeding on non-degrading glass slides but could not be provoked by inhibition of the protein kinase R-like endoplasmic reticulum kinase. By investigating the influence of the disjunct surface-near effects of the Mg degradation on cell proliferation, an increased pH was found to be a main initiator of Mg degradation-dependent tumor cell proliferation inhibition.

Breast cancer vaccines: New insights into immunomodulatory and nano-therapeutic approaches

Breast cancer (BC) is known to be a highly heterogeneous disease that is clinically subdivided into four primary molecular subtypes, each having distinct morphology and clinical implications. These subtypes are principally defined by hormone receptors and other proteins involved (or not involved) in BC development. BC therapeutic vaccines [including peptide-based vaccines, protein-based vaccines, nucleic acid-based vaccines (DNA/RNA vaccines), bacterial/viral-based vaccines, and different immune cell-based vaccines] have emerged as an appealing class of cancer immunotherapeutics when used alone or combined with other immunotherapies. Employing the immune system to eliminate BC cells is a novel therapeutic modality. The benefit of active immunotherapies is that they develop protection against neoplastic tissue and readjust the immune system to an anti-tumor monitoring state. Such immunovaccines have not yet shown effectiveness for BC treatment in clinical trials. In recent years, nanomedicines have opened new windows to increase the effectiveness of vaccinations to treat BC. In this context, some nanoplatforms have been designed to efficiently deliver molecular, cellular, or subcellular vaccines to BC cells, increasing the efficacy and persistence of anti-tumor immunity while minimizing undesirable side effects. Immunostimulatory nano-adjuvants, liposomal-based vaccines, polymeric vaccines, virus-like particles, lipid/calcium/phosphate nanoparticles, chitosan-derived nanostructures, porous silicon microparticles, and selenium nanoparticles are among the newly designed nanostructures that have been used to facilitate antigen internalization and presentation by antigen-presenting cells, increase antigen stability, enhance vaccine antigenicity and remedial effectivity, promote antigen escape from the endosome, improve cytotoxic T lymphocyte responses, and produce humoral immune responses in BC cells. Here, we summarized the existing subtypes of BC and shed light on immunomodulatory and nano-therapeutic strategies for BC vaccination. Finally, we reviewed ongoing clinical trials on BC vaccination and highlighted near-term opportunities for moving forward.

The crosstalk of the human microbiome in breast and colon cancer: A metabolomics analysis

The human microbiome's role in colon and breast cancer is described in this review. Understanding how the human microbiome and metabolomics interact with breast and colon cancer is the chief area of this study. First, the role of the gut and distal microbiome in breast and colon cancer is investigated, and the direct relationship between microbial dysbiosis and breast and colon cancer is highlighted. This work also focuses on the many metabolomic techniques used to locate prospective biomarkers, make an accurate diagnosis, and research new therapeutic targets for cancer treatment. This review clarifies the influence of anti-tumor medications on the microbiota and the proactive measures that can be taken to treat cancer using a variety of therapies, including radiotherapy, chemotherapy, next-generation biotherapeutics, gene-based therapy, integrated omics technology, and machine learning.

Proteomic analysis of arylamine N-acetyltransferase 1 knockout breast cancer cells: Implications in immune evasion and mitochondrial biogenesis

Previous studies have shown that inhibition or depletion of N-acetyltransferase 1 (NAT1) in breast cancer cell lines leads to growth retardation both in vitro and in vivo, suggesting that NAT1 contributes to rapid growth of breast cancer cells. To understand molecular and cellular processes that NAT1 contributes to and generate novel hypotheses in regard to NAT1's role in breast cancer, we performed an unbiased analysis of proteomes of parental MDA-MB-231 breast cancer cells and two separate NAT1 knockout (KO) cell lines. Among 4890 proteins identified, 737 proteins were found significantly (p < 0.01) upregulated, and 651 proteins were significantly (p < 0.01) downregulated in both NAT1 KO cell lines. We performed enrichment analyses to identify Gene Ontology biological processes, molecular functions, and cellular components that were enriched in each data set. Among the proteins upregulated in NAT1 KO cells, pathways associated with MHC (major histocompatibility complex) I-mediated antigen presentation were significantly enriched. This raises an interesting and new hypothesis that upregulation of NAT1 in breast cancer cells may aid them evade immune detection. Multiple pathways involved in mitochondrial functions were collectively downregulated in NAT1 KO cells, including multiple subunits of mitochondrial ATP synthase (Complex V of the electron transport chain). This was accompanied by a reduction in cell cycle-associated proteins and an increase in pro-apoptotic pathways in NAT1 KO cells, consistent with reported observations that NAT1 KO cells exhibit a slower growth rate both in vitro and in vivo. Thus, mitochondrial dysfunction in NAT1 KO cells likely contributes to growth retardation.

The Variable Nature of Vitamin C—Does It Help When Dealing with Coronavirus?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still spreading worldwide. For this reason, new treatment methods are constantly being researched. Consequently, new and already-known preparations are being investigated to potentially reduce the severe course of coronavirus disease 2019 (COVID-19). SARS-CoV-2 infection induces the production of pro-inflammatory cytokines and acute serum biomarkers in the host organism. In addition to antiviral drugs, there are other substances being used in the treatment of COVID-19, e.g., those with antioxidant properties, such as vitamin C (VC). Exciting aspects of the use of VC in antiviral therapy are its antioxidant and pro-oxidative abilities. In this review, we summarized both the positive effects of using VC in treating infections caused by SARS-CoV-2 in the light of the available research. We have tried to answer the question as to whether the use of high doses of VC brings the expected benefits in the treatment of COVID-19 and whether such treatment is the correct therapeutic choice. Each case requires individual assessment to determine whether the positives outweigh the negatives, especially in the light of populational studies concerning the genetic differentiation of genes encoding the solute carriers responsible forVC adsorption. Few data are available on the influence of VC on the course of SARS-CoV-2 infection. Deducing from already-published data, high-dose intravenous vitamin C (HDIVC) does not significantly lower the mortality or length of hospitalization. However, some data prove, among other things, its impact on the serum levels of inflammatory markers. Finally, the non-positive effect of VC administration is mainly neutral, but the negative effect is that it can result in urinary stones or nephropathies.

Molecular Oncology of Bladder Cancer from Inception to Modern Perspective

Within the last forty years, seminal contributions have been made in the areas of bladder cancer (BC) biology, driver genes, molecular profiling, biomarkers, and therapeutic targets for improving personalized patient care. This overview includes seminal discoveries and advances in the molecular oncology of BC. Starting with the concept of divergent molecular pathways for the development of low- and high-grade bladder tumors, field cancerization versus clonality of bladder tumors, cancer driver genes/mutations, genetic polymorphisms, and bacillus Calmette-Guérin (BCG) as an early form of immunotherapy are some of the conceptual contributions towards improving patient care. Although beginning with a promise of predicting prognosis and individualizing treatments, "-omic" approaches and molecular subtypes have revealed the importance of BC stem cells, lineage plasticity, and intra-tumor heterogeneity as the next frontiers for realizing individualized patient care. Along with urine as the optimal non-invasive liquid biopsy, BC is at the forefront of the biomarker field. If the goal is to reduce the number of cystoscopies but not to replace them for monitoring recurrence and asymptomatic microscopic hematuria, a BC marker may reach clinical acceptance. As advances in the molecular oncology of BC continue, the next twenty-five years should significantly advance personalized care for BC patients.

Association of XRCC3, XRCC4, BAX, and BCL-2 Polymorphisms with the Risk of Breast Cancer

Background

Breast cancer is the most common malignancy in women. Genetic risk factors associated with breast cancer incidence have been identified.

Aims

This study is aimed at determining the association of XRCC3 Thr241Met (rs861539), XRCC4 G(-1394) T (rs6869366) DNA repair and BAX G(-248) A (rs4645878), and BCL2 C(-938) A (rs2279115) apoptotic gene polymorphisms with breast cancer.

Materials and Methods

Genetic analysis was performed using peripheral blood samples. Gene polymorphisms were detected by using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. 175 patients and 158 healthy controls were enrolled in the study.

Results

Breast cancer risk was 5.43 times more in individuals with AA genotype of Bax G(-248) A (rs4645878) (P = 0.002). The risk of metastasis was 11 times with this genotype. It was associated with 6 times more risk of having a tumor larger than 2 cm. The risk of breast cancer was 2.77 times more in individuals carrying the Met/Met genotype of XRCC3 Thr241Met (rs861539) (P = 0.009). The risk of having advanced clinical stage (stage III+IV) with the Met/Met genotype was 4 times more increased. No relationship with breast cancer was found with XRCC4 G(-1394) T (rs6869366) and BCL2 C(-938) A (rs2279115) gene polymorphisms.

Conclusion

Multicenter trials using subjects with genetic variations are needed to establish the relationship between breast cancer and single gene polymorphism.

Genome-wide association study on milk production and somatic cell score for Thai dairy cattle using weighted single-step approach with random regression test-day model

Genome-wide association studies are a powerful tool to identify genomic regions and variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. The objectives of this study were to identify genomic regions as well as genes and pathways associated with the first-lactation milk, fat, protein, and total solid yields; fat, protein, and total solid percentage; and somatic cell score (SCS) in a Thai dairy cattle population. Effects of SNPs were estimated by a weighted single-step GWAS, which back-solved the genomic breeding values predicted using single-step genomic BLUP (ssGBLUP) fitting a single-trait random regression test-day model. Genomic regions that explained at least 0.5% of the total genetic variance were selected for further analyses of candidate genes. Despite the small number of genotyped animals, genomic predictions led to an improvement in the accuracy over the traditional BLUP. Genomic predictions using weighted ssGBLUP were slightly better than the ssGBLUP. The genomic regions associated with milk production traits contained 210 candidate genes on 19 chromosomes [Bos taurus autosome (BTA) 1 to 7, 9, 11 to 16, 20 to 21, 26 to 27 and 29], whereas 21 candidate genes on 3 chromosomes (BTA 11, 16, and 21) were associated with SCS. Many genomic regions explained a small fraction of the genetic variance, indicating polygenic inheritance of the studied traits. Several candidate genes coincided with previous reports for milk production traits in Holstein cattle, especially a large region of genes on BTA14. We identified 141 and 5 novel genes related to milk production and SCS, respectively. These novel genes were also found to be functionally related to heat tolerance (e.g., SLC45A2, IRAG1, and LOC101902172), longevity (e.g., SYT10 and LOC101903327), and fertility (e.g., PAG1). These findings may be attributed to indirect selection in our population. Identified biological networks including intracellular cell transportation and protein catabolism implicate milk production, whereas the immunological pathways such as lymphocyte activation are closely related to SCS. Further studies are required to validate our findings before exploiting them in genomic selection.

Classification and Treatment of Diseases in the Age of Genome Medicine Based on Pathway Pathology

The focus of pathology as a biomedical discipline is the identification of the pathomechanisms of diseases and the integration of this knowledge into routine diagnosis and classification. Standard tools are macroscopic and microscopic analysis complemented by immunohistochemistry and molecular pathology. So far, classification has been based on the paradigm of cellular pathology established by Rudolf Virchow and others more than 150 years ago, stating that diseases originate from diseased cells. This dogma is meanwhile challenged by the fact that cells can be fully reprogrammed. Many diseases are nowadays considered to originate from undifferentiated stem cells, induced into a diseased state by genetic or epigenetic alterations. In addition, the completion of the Human Genome Project, with the identification of more than 20.000 genes and a much higher number of gene variants and mutations, led to the concept that diseases are dominated by genetics/epigenetics rather than cells of origin. The axiom of cellular pathology, however, still holds true, as cells are the smallest animate units from which diseases originate. Medical doctors and researchers nowadays have to deal with a tremendous amount of data. The International Classification of Diseases will expand from 14.400 entities/codes in ICD-10 to more than 55.000 in ICD-11. In addition, large datasets generated by “genomics“, e.g., whole-genome sequencing, expression profiling or methylome analysis, are meanwhile not only applied in research but also introduced into clinical settings. It constitutes a major task to incorporate all the data into routine medical work. Pathway pathology may help solve this problem. It is based on the realization that diseases are characterized by three essential components: (i) cells of origin/cellular context and (ii) the alteration of cellular as well as (iii) molecular/signal transduction pathways. The concept is illustrated by elaborating on two key cellular pathways, i.e., the cellular senescence of normal cells and the immortality of cancer cells, and by contrasting single cell/single pathway diseases, such as mycoplasma and coughing pneumonia, with complex diseases such as cancer, with multiple cell types as well as multiple affected cellular and signaling pathways. Importantly, the concept of pathway pathology is not just intended to classify disease, but also to conceive new treatment modalities. This article is dedicated to Dr. Leonard Hayflick, who made basic discoveries in pathway pathology not only by identifying cells causing disease (Mycoplasma pneumoniae) and establishing cell strains for treating disease (WI-38 for viral vaccines), but also by first describing cellular senescence and immortality.

The 21-Gene Recurrence Score in Special Histologic Subtypes of Breast Cancer: A Population-Based Study

CONTEXT.—

Recurrence score (RS) testing was developed and validated in invasive ductal and rare lobular carcinomas, although it is used for all special types of breast cancers.

OBJECTIVE.—

To determine association of histologic type (HT) and RS, specifically high-risk RS.

DESIGN.—

We used RSs linked to Surveillance, Epidemiology, and End Results program registries of invasive breast cancers diagnosed in 2004 through 2015. Multivariable logistic regression was used to evaluate association between HT and high-risk RS. Relationships between HT and low-, intermediate-, and high-risk RS were compared with χ2 test. Kaplan-Meier curves were compared using log-rank test.

RESULTS.—

A total of 110 318 patients had RS testing. Of these, 23 220 (21%) had low, 70 822 (64.2%) intermediate, and 16 276 (14.8%) high RS. Histologic types were 80 476 (73%) ductal, 12 713 (11.5%) lobular, 12 449 (11.3%) mixed, 2151 (2%) mucinous, 610 (0.6%) tubular 382 (0.4%) micropapillary, 365 (0.3%) salivary, 208 (0.2%) papillary, 49 (0.04%) medullary, 26 (0.02%) metaplastic, 26 (0.02%) neuroendocrine, and 863 (0.8%) unknown. The distribution of low-, intermediate-, and high-risk RS was significantly different among HTs. Higher percentages of high-risk RS were identified in patients with ductal, medullary, and metaplastic types (P < .001). The odds of having high-risk RS were lower for some HTs, including micropapillary, after multivariable adjustment (P < .05). The low number of estrogen receptor-positive medullary and metaplastic carcinomas tested had higher odds of having high-risk RS. In T1 and T2 tumors, when ductal, lobular, mixed, and other types combined were compared, the mortality was different.

CONCLUSIONS.—

This population-based study of RS in HTs showed high-risk RSs are identified in traditionally good prognostic subtypes. Micropapillary carcinoma has lower odds of high-risk RS even after multivariable adjustment.

Cytotoxicity and Cellular Death Modality of Surface-Decorated Gold Nanorods against a Panel of Breast Cancer Cell Lines

Herein, the antiproliferative effect of surface-decorated gold nanorods (GNRs) was investigated against three different breast cancer cell lines. The results indicate that the cell lines exhibited different biological responses and death modalities toward the treatment. The cell lines exhibited similar cellular uptake of the nanoparticles; however, MDA-MB-231 demonstrated the highest cytotoxicity compared to other cell lines upon treatment with GNRs. The expression of the CDH1 gene, which is involved in cell adhesion and metastasis, was dramatically increased in treated MDA-MB-231 cells compared to other cell lines. Early apoptosis and late apoptosis are the dominant cellular death modalities of MDA-MB-231 cells upon treatment with GNRs.

Variable selection for censored data using Modified Correlation Adjusted coRrelation (MCAR) scores

Dealing with high-dimensional censored data is very challenging because of the complexities in data structure. This article focuses on developing a variable selection procedure for censored high-dimensional data with the AFT models using the Modified Correlation Adjusted coRrelation (MCAR) scores method. The latter is developed based on CAR scores method that provides a canonical ordering that encourages grouping of correlated predictors and down-weights antagonistic variables. The proposed MCAR scores method is developed as an extension of the CAR scores method using NOVEL integration of the sample and threshold estimator of the correlation matrix as suggested by Huang and Frylewicz. The proposed MCAR exhibits computationally more efficient estimates under model sparsity and can provide a canonical ordering among the predictors. The MCAR method is a greedy method that is also easy to understand and can perform estimation and variable selection simultaneously. Performances of variable selection by the MCAR method have been compared with other existing regularized techniques in literature-such as the lasso, elastic net and with a machine learning technique called boosting and with the censored CAR by a number of simulation studies and a real microarray data set called diffuse large-B-cell lymphoma. Results indicate that when correlation exists among the covariates, the MCAR method outperforms all five techniques while for uncorrelated data, the MCAR performs quite similar to the CAR method but clearly outperforms the other three methods. The empirical study further reveals that the MCAR method exhibits the best predictive performance among the methods.

Immune Crosstalk Between Lymph Nodes and Breast Carcinomas, With a Focus on B Cells

Lymph nodes (LNs) are highly organized secondary lymphoid organs, and reflective of immune responses to infection, injuries, or the presence of cancer. Extensive molecular and morphological analyses of immune and stromal features in tumors and LNs of breast cancer patients have revealed novel patterns indicative of disease progression. Within LNs, there are dynamic structures called germinal centers (GCs), that act as the immunological hubs for B cell development and generation of affinity matured memory B and antibody-producing plasma cells. Acting as a bridge between systemic and local immunity, associations are observed between the frequency of GCs within cancer-free LNs, the levels of stromal tumor infiltrating lymphocytes, and cancer progression. Scattered throughout the tumor microenvironment (TME) or aggregated in clusters forming tertiary lymphoid structures (TLS), the occurrence of tumor infiltrating B cells (TIL-Bs) has been linked mostly to superior disease trajectories in solid cancers. Recent TIL-Bs profiling studies have revealed a plethora of different TIL-B populations, their functional roles, and whether they are derived from GC reactions in the LN, and/or locally from GC-like structures within the TME remains to be investigated. However, parallels between the immunogenic nature of LNs as a pre-metastatic niche, TIL-B populations within the TME, and the presence of TLS will help to decipher local and widespread TIL-Bs responses and their influence on cancer progression to the lymphatics. Therapies that enhance TIL-Bs responses in the LN GC and/or in GC-like structures in the TME are thus emerging management strategies for breast and other cancer patients.

Machine learning-integrated omics for the risk and safety assessment of nanomaterials

With the advancement in nanotechnology, we are experiencing transformation in world order with deep insemination of nanoproducts from basic necessities to advanced electronics, health care products and medicines. Therefore, nanoproducts, however, can have negative side effects and must be strictly monitored to avoid negative outcomes. Future toxicity and safety challenges regarding nanomaterial incorporation into consumer products, including rapid addition of nanomaterials with diverse functionalities and attributes, highlight the limitations of traditional safety evaluation tools. Currently, artificial intelligence and machine learning algorithms are envisioned for enhancing and improving the nano-bio-interaction simulation and modeling, and they extend to the post-marketing surveillance of nanomaterials in the real world. Thus, hyphenation of machine learning with biology and nanomaterials could provide exclusive insights into the perturbations of delicate biological functions after integration with nanomaterials. In this review, we discuss the potential of combining integrative omics with machine learning in profiling nanomaterial safety and risk assessment and provide guidance for regulatory authorities as well.

The Dual Function of KDM5C in Both Gene Transcriptional Activation and Repression Promotes Breast Cancer Cell Growth and Tumorigenesis

Emerging evidence suggested that epigenetic regulators can exhibit both activator and repressor activities in gene transcriptional regulation and disease development, such as cancer. However, how these dual activities are regulated and coordinated in specific cellular contexts remains elusive. Here, it is reported that KDM5C, a repressive histone demethylase, unexpectedly activates estrogen receptor alpha (ERα)-target genes, and meanwhile suppresses type I interferons (IFNs) and IFN-stimulated genes (ISGs) to promote ERα-positive breast cancer cell growth and tumorigenesis. KDM5C-interacting protein, ZMYND8, is found to be involved in both processes. Mechanistically, KDM5C binds to active enhancers and recruits the P-TEFb complex to activate ERα-target genes, while inhibits TBK1 phosphorylation in the cytosol to repress type I IFNs and ISGs. Pharmacological inhibition of both ERα and KDM5C is effective in inhibiting cell growth and tumorigenesis. Taken together, it is revealed that the dual activator and repressor nature of an epigenetic regulator together contributes to cancer development.

Chemopreventive and Anticancer Property of Selenoproteins in Obese Breast Cancer

Obesity is a significant risk factor for various cancers including breast cancer resulting in an increased risk of recurrence as well as morbidity and mortality. Extensive studies on various pathways have been successful in establishing a biological relationship between obesity and breast cancer. The molecular classification of breast cancer includes five groups each having different responses to treatment. Increased levels of inflammatory cytokines seen in obese conditions drive the pro-proliferative pathways, such as the influx of macrophages, angiogenesis, and antiapoptotic pathways. Increased peripheral aromatization of androgens by aromatase increases the circulating estrogen levels which are also responsible for the association of obesity with breast cancer. Also, increased oxidative stress due to chronic low-grade inflammation in obese women plays an important role in carcinogenesis. Despite the availability of safe and effective treatment options for breast cancer, obese women are at increased risk of adverse outcomes including treatment-related toxicities. In the recent decade, selenium compounds have gained substantial interest as chemopreventive and anticancer agents. The chemical derivatives of selenium include inorganic and organic compounds that exhibit pro-oxidant properties and alter cellular redox homeostasis. They target more than one metabolic pathway by thiol modifications, induction of reactive oxygen species, and chromatin modifications to exert their chemopreventive and anticancer activities. The primary functional effectors of selenium that play a significant role in human homeostasis are selenoproteins like glutathione peroxidase, thioredoxin reductase, iodothyronine deiodinases, and selenoprotein P. Selenoproteins play a significant role in adipose tissue physiology by modulating preadipocyte proliferation and adipogenic differentiation. They correlate negatively with body mass index resulting in increased oxidative stress that may lead to carcinogenesis in obese individuals. Methylseleninic acid effectively suppresses aromatase activation thus reducing the estrogen levels and acting as a breast cancer chemopreventive agent. Adipose-derived inflammatory mediators influence the selenium metabolites and affect the proliferation and metastatic properties of cancer cells. Recently selenium nanoparticles have shown potent anticancer activity which may lead to a major breakthrough in the management of cancers caused due to multiple pathways. In this review, we discuss the possible role of selenoproteins as chemopreventive and an anticancer agent in obese breast cancer.

Management of patients with BRCA mutation from the point of view of a breast surgeon

Germ-line mutation in BRCA (BReast CAncer gene) 1 or BRCA2 are found in 3–4% of all women with breast cancer. These patients have a significant increased risk of breast and ovarian cancer. They are often younger when diagnosed with the mutation, and the possible breast cancer they get is often aggressive with inferior outcome. There are risk reducing strategies, and the most powerful strategy is risk reducing surgery, both risk reducing bilateral mastectomy (RRM) and risk reducing bilateral salpino-oophorectomy (PBSO). This review is meant to address breast surgery in patients with germline BRCA mutation. The guidelines and techniques applied is under continuous change and it is important for the clinicians to be well informed to provide the patient with the information needed for them to make an informed decision on what risk strategy to choose.

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Patients with germ-line mutation in BRCA1 or BRCA2 have a significant increased risk of breast and ovarian cancer.

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There are different risk reducing strategies and the most powerful strategy is risk-reducing surgery, both risk reducing bilateral mastectomy and risk reducing bilateral salpingo-oophorectomy.

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Guidelines and techniques for the risk reducing surgery of the breast are under continuous change and improvement.

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Breast conserving therapy is not associated with worse survival and is a good option for a BRCA mutation carrier diagnosed with breast cancer. Risk-reducing mastectomy can be performed in a later setting.

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The management of BRCA mutation carriers, both affected and unaffected, should be performed in a multidisciplinary team. Physicians need to be systematically educated and updated on the most recent literature.

Global Protease Activity Profiling Identifies HER2-Driven Proteolysis in Breast Cancer

Differential expression of extracellular proteases and endogenous protease inhibitors has been associated with distinct molecular subtypes of breast cancer. However, due to the tight post-translational regulation of protease activity, protease expression-level data alone are not sufficient to understand the role of proteases in malignant transformation. Therefore, we hypothesized that global profiles of extracellular protease activity could more completely reflect differences observed at the transcriptional level in breast cancer and that subtype-associated protease activity may be leveraged to identify specific proteases that play a functional role in cancer signaling. Here, we used a global peptide library-based approach to profile the activities of proteases within distinct breast cancer subtypes. Analysis of 3651 total peptide cleavages from a panel of well-characterized breast cancer cell lines demonstrated differences in proteolytic signatures between cell lines. Cell line clustering based on protease cleavages within the peptide library expanded upon the expected classification derived from transcriptional profiling. An isogenic cell line model developed to further interrogate proteolysis in the HER2 subtype revealed a proteolytic signature consistent with activation of TGF-β signaling. Specifically, we determined that a metalloprotease involved in TGF-β signaling, BMP1, was upregulated at both the protein (2-fold, P = 0.001) and activity (P = 0.0599) levels. Inhibition of BMP1 and HER2 suppressed invasion of HER2-expressing cells by 35% (P < 0.0001), compared to 15% (P = 0.0086) observed in cells where only HER2 was inhibited. In summary, through global identification of extracellular proteolysis in breast cancer cell lines, we demonstrate subtype-specific differences in protease activity and elucidate proteolysis associated with HER2-mediated signaling.