Breast cancer diagnosis: Imaging techniques and biochemical markers

GPD1 inhibits the carcinogenesis of breast cancer through increasing PI3K/AKT-mediated lipid metabolism signaling pathway

Glycerol 3-phosphate dehydrogenase 1 (GPD1) acts as a tumor suppressor in various types of cancer. However, the mechanisms of GPD1 anti-tumor remain unclear in breast cancer. This study aims to explore the function and clinical relevance of GPD1 in breast cancer. We confirmed that GPD1 inhibited the ability of proliferation, migration, and invasion in GPD1 overexpression breast cancer cells by CCK-8, wound healing, and Transwell assays, respectively. We found that GPD1 overexpression activated the lipid synthesis pathway and PI3K/AKT signaling pathway. The inhibitory effect of GPD1 on breast cancer cells was also weakened after treatment with LY294002, a PI3K/AKT pathway inhibitor. These results indicated that GPD1 suppressed the carcinogenesis of breast cancer through increasing PI3K/AKT-mediated lipid signaling pathways. Meanwhile, we detected that the relationship between GPD1 level and survival rate presents a positive correlation in breast cancer patients from the Cancer Genome Atlas (TCGA) database. Therefore, GPD1 can be a prognostic biomarker and target in developing therapeutic strategies for breast cancer patients.

Vaccines in Breast Cancer: Challenges and Breakthroughs

Breast cancer is a problem for women's health globally. Early detection techniques come in a variety of forms ranging from local to systemic and from non-invasive to invasive. The treatment of cancer has always been challenging despite the availability of a wide range of therapeutics. This is either due to the variable behaviour and heterogeneity of the proliferating cells and/or the individual's response towards the treatment applied. However, advancements in cancer biology and scientific technology have changed the course of the cancer treatment approach. This current review briefly encompasses the diagnostics, the latest and most recent breakthrough strategies and challenges, and the limitations in fighting breast cancer, emphasising the development of breast cancer vaccines. It also includes the filed/granted patents referring to the same aspects.

Intermodal correlation of quantitative CT-data and MRI-biomarkers derived from synchronous spectral CT-maps and breast MRI-examinations with molecular biomarkers in invasive ductal breast carcinomas

OBJECTIVE

To asses the correlation of data derived from dual-layer (DL)-CT material-maps and breast MRI data with molecular biomarkers in invasive breast carcinomas.

METHODS

All patients at the University Breast Cancer Center who underwent a clinically indicated DLCT-scan and a breast MRI for staging of invasive ductal breast cancer from 2016 to 2020 were prospectively included. Iodine concentration-maps, and Zeffective-maps were reconstructed from the CT-datasets. T1w- and T2w-signal intensities, ADC and the clustered shapes of the dynamic-curves (washout, plateau, persistent) were derived from the MRI-datasets. ROI-based evaluations of the cancers and the reference "musculature" were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Statistical analysis was essentially descriptive using Spearmańs rank correlation and (multivariable) partial correlation.

RESULTS

The signal intensities measured in the 3rd phase of the contrast dynamics correlated at an intermediate level of significance with the iodine content and the Zeffective-values derived from the breast target lesions (Spearmańs rank correlation-coefficient r = 0.237/0.236, p = 0.002/0.003). The bivariate and the multivariate analyses displayed correlations of an intermediate significance level of the iodine content and the Zeff-values measured in the breast target lesions with immunhistochemical subtyping (r = 0.211-0.243, p = 0.002-0.009, respectively). The Zeff-values showed the strongest correlations when normalized to the values measured in the musculature and in the aorta (r = -0.237 to -0.305, r=<0.001-0.003). The MRI-assessments showed correlations of intermediate to high significance and low to intermediate significance between the ratios of the T2w-signal intensities and the trends of the dynamic curves measured in the breast target lesions and in musculature and immunohistochemical cancer subtyping, respectively (T2w: r = 0.232-0.249, p = 0.003/0.002; dynamics: r = -0.322/-0.245, p=<0.001/0.002). The ratios of the clustered trends of the dynamic curves measured in the breast target lesions and in musculature correlated with tumor grading on intermediate significance level (r = -0.213 and -0.194, p = 0.007/0.016) and with Ki-67 on a low significance level (bivariate analysis: r = -0.160, p = 0.040). There was only a weak correlation between the ADC-values measured in the breast target lesions and HER2-expression (bivariate ansalysis: r = 0.191, p = 0.030).

CONCLUSIONS

Our preliminary results indicate that evaluation of perfusion based DLCT-data and MRI-biomarkers show correlations with the immunhistochemical subtyping of invasive ductal breast carcinomas. Further clinical research is warranted in order to validate the value of the results and define clinical situations in which the use of the described DLCT-biomaker and MRI biomarkers may be helpful in clinical patient care.

Role of synaptotagmin 13 (SYT13) in promoting breast cancer and signaling pathways

PURPOSE

Breast cancer is one of the leading causes of tumor death worldwide in female, and the five-year overall survival of breast cancer patients remains poor. It is an urgent need to seek novel target for its treatment. Synaptotagmin 13 (SYT13) is a synaptic vesicle transporting protein that regulates the malignant phenotypes of various cancers. However, its role in breast cancer is still unclear. The current study aimed to investigate the effects of SYT13 on the progression of breast cancer.

METHODS

Twenty-five pairs of breast cancer tissues and non-tumor tissues were obtained to assess the expression of SYT13. We manually modified the expression of SYT13 in MCF-7 and MDA-MB-231 cells. CCK-8 assay, EdU staining, and cell cycle analysis were carried out to measure the proliferated ability of cells. Annexin V/PI and TUNEL assays were used to detect the apoptotic ability of cells. Wound healing and transwell assays were employed to evaluate the migrated and invasive ability of breast cancer cells.

RESULTS

The results revealed that the mRNA and protein levels of SYT13 were higher in breast cancer tissues and cell lines. Knockdown of SYT13 inhibited the cell proliferation and induced cell cycle arrest in G1 phase of MCF-7 cells by downregulating cyclin D1 and CDK4, as well as upregulating p21. The migration and invasion of MCF-7 cells were repressed by the loss of SYT13 via the gain of E-cadherin and the loss of vimentin. Overexpression of SYT13 in MDA-MB-231 cells led to the opposite effects. Silencing of SYT13 induced the apoptosis ability of MCF-7 cells by the upregulation of bax and the downregulation of bcl-2. Moreover, we found that SYT13 depletion suppressed the FAK/AKT signaling pathway. PF573228 (a FAK inhibitor) and MK2206 (an AKT inhibitor) reversed the SYT13 overexpression-induced promotion of proliferation, migration, and invasion of MDA-MB-231 cells.

CONCLUSION

The results indicated that SYT13 promoted the malignant phenotypes of breast cancer cells by the activation of FAK/AKT signaling pathway.

Tumor infiltrating lymphocytes and radiological picture of the tumor

Tumor microenvironment (TME) is a complex entity that includes besides the tumor cells also a whole range of immune cells. Among various populations of immune cells infiltrating the tumor, tumor infiltrating lymphocytes (TILs) are a population of lymphocytes characterized by high reactivity against the tumor component. As, TILs play a key role in mediating responses to several types of therapy and significantly improve patient outcomes in some cancer types including for instance breast cancer and lung cancer, their assessment has become a good predictive tool in the evaluation of potential treatment efficacy. Currently, the evaluation of the density of TILs infiltration is performed by histopathological. However, recent studies have shed light on potential utility of several imaging methods, including ultrasonography, magnetic resonance imaging (MRI), positron emission tomography-computed tomography (PET-CT), and radiomics, in the assessment of TILs levels. The greatest attention concerning the utility of radiology methods is directed to breast and lung cancers, nevertheless imaging methods of TILs are constantly being developed also for other malignancies. Here, we focus on reviewing the radiological methods used to assess the level of TILs in different cancer types and on the extraction of the most favorable radiological features assessed by each method.

The value, diagnostic efficacy and clinical significance of functional magnetic resonance imaging in evaluating the efficacy of neoadjuvant chemotherapy in patients with triple negative breast cancer

Background

Breast cancer (BC) is a common malignant tumor in female. In recent years, with the change of fertility pattern and lifestyle, the incidence of breast cancer is increasing year by year, seriously endangering the health and life of women. MRI is suitable for follow-up evaluation of the course of neoadjuvant chemotherapy in LABC, but there are few related studies and reports. Based on the above background, it is necessary to further evaluate the value of functional magnetic resonance imaging in neoadjuvant chemotherapy in patients with triple negative breast cancer, so as to lay a theoretical foundation for the popularization and application of this detection method. Based on this, this study was to explore the value, diagnostic efficacy and clinical importance of functional magnetic resonance imaging in evaluating the efficacy of neoadjuvant chemotherapy in patients with triple negative breast cancer.

Methods

A total of 62 patients with triple-negative breast cancer who received neoadjuvant chemotherapy in our hospital from September 2017 to September 2022 were selected. To compare the differences of functional magnetic resonance imaging (fMRI) between effective and ineffective patients with neoadjuvant chemotherapy, the related data were statistically analyzed.

Results

There was no significant difference between the mode of tumor withdrawal and the pathological complete remission of tumor tissue (P>0.05). There was no significant difference in anti-Trop-2 antibody-drug conjugates (ADC) data before and after chemotherapy between over-expressed patients with human epidermal growth factor receptor-2 (HER-2) and non-over-expressed patients with HER-2 (P>0.05). The levels of ADC and Δ ADC in pathological complete remission patients after chemotherapy were significantly higher than those in non-pathological complete remission patients (P<0.05). Using the ΔADC value as the evaluation parameter, the pathological response of tumor tissue was classified as the "gold standard" to draw the ROC curve, the area under curve (AUC) was 0.673, the cut-off of ΔADC to evaluate the significant response of tumor tissue after chemotherapy was 1.418, the sensitivity of evaluating the efficacy was 71.9%, and the specificity was 55.0%.

Conclusion

Functional magnetic resonance imaging (fMRI) has diagnostic value for neoadjuvant chemotherapy in patients with triple negative breast cancer. According to the change of ADC value, the curative effect can be predicted early and the treatment strategy can be adjusted in time.

Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence

BACKGROUND

Breast cancer has become the most common malignant tumour worldwide. Distant metastasis is one of the leading causes of breast cancer-related death. To verify the performance of clinicomics-guided distant metastasis risk prediction for breast cancer via artificial intelligence and to investigate the accuracy of the created prediction models for metachronous distant metastasis, bone metastasis and visceral metastasis.

METHODS

We retrospectively enrolled 6703 breast cancer patients from 2011 to 2016 in our hospital. The figures of magnetic resonance imaging scanning and ultrasound were collected, and the figures features of distant metastasis in breast cancer were detected. Clinicomics-guided nomogram was proven to be with significant better ability on distant metastasis prediction than the nomogram constructed by only clinical or radiographic data.

RESULTS

Three clinicomics-guided prediction nomograms on distant metastasis, bone metastasis and visceral metastasis were created and validated. These models can potentially guide metachronous distant metastasis screening and lead to the implementation of individualized prophylactic therapy for breast cancer patients.

CONCLUSION

Our study is the first study to make cliniomics a reality. Such cliniomics strategy possesses the development potential in artificial intelligence medicine.

Enhanced characterization of breast cancer phenotypes using Raman micro-spectroscopy on stainless steel substrate

Biochemical insights into varying breast cancer (BC) phenotypes can provide a fundamental understanding of BC pathogenesis, while identifying novel therapeutic targets. Raman spectroscopy (RS) can gauge these biochemical differences with high specificity. For routine RS, cells are traditionally seeded onto calcium fluoride (CaF₂) substrates that are costly and fragile, limiting its widespread adoption. Stainless steel has been interrogated previously as a less expensive alternative to CaF₂ substrates, while reporting increased Raman signal intensity than the latter. We sought to further investigate and compare the Raman signal quality measured from stainless steel versus CaF₂ substrates by characterizing different BC phenotypes with altered human epidermal growth factor receptor 2 (HER2) expression. Raman spectra were obtained on stainless steel and CaF₂ substrates for HER2 negative cells - MDA-MB-231, MDA-MB-468 and HER2 overexpressing cells - AU565, SKBr3. Upon analyzing signal-to-noise ratios (SNR), stainless steel provided a stronger Raman signal, improving SNR by 119% at 1450 cm^-1 and 122% at 2925 cm^-1 on average compared to the CaF₂ substrate. Utilizing only 22% of laser power on sample relative to the CaF₂ substrate, stainless steel still yielded improved spectral characterization over CaF₂, achieving 96.0% versus 89.8% accuracy in BC phenotype discrimination and equivalent 100.0% accuracy in HER2 status classification. Spectral analysis further highlighted increased lipogenesis and altered metabolism in HER2 overexpressing cells, which was subsequently visualized with coherent anti-Stokes Raman scattering microscopy. Our findings demonstrate that stainless steel substrates deliver improved Raman signal and enhanced spectral characterization, underscoring its potential as a cost-effective alternative to CaF₂ for non-invasively monitoring cellular biochemical dynamics in translational cancer research.

Development and validation of a nomogram to predict Chinese breast cancer risk based on clinical serum biomarkers

Background: This study investigated and compared clinical serum biomarkers and developed a diagnostic nomogram for breast cancer. Methods: A total of 1224 breast cancer and 1280 healthy controls were enrolled. Univariate and multivariate analyses were performed to identify factors and a nomogram was developed. Discrimination, accuracy and clinical utility values were evaluated by receiver operating characteristic, Hosmer-Lemeshow, calibration plots, decision curve analysis and clinical impact plots. Results: carcinoembryonic antigen, CA125, CA153, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, fibrinogen and platelet distributing width were effectively identified to predict breast cancer. The nomogram showed the area under the curve of 0.708 and 0.710 in the training and validation set. Calibration plots, Hosmer-Lemeshow, decision curve analysis and clinical impact plots confirmed great accuracy and clinical utility. Conclusion: We developed and validated a nomogram that is effectively used for risk prediction of Chinese breast cancer.

Contrast-Enhanced Spectral Mammography in the Evaluation of Breast Microcalcifications: Controversies and Diagnostic Management

The aim of this study was to evaluate the diagnostic performance of contrast-enhanced spectral mammography (CESM) in predicting breast lesion malignancy due to microcalcifications compared to lesions that present with other radiological findings. Three hundred and twenty-one patients with 377 breast lesions that underwent CESM and histological assessment were included. All the lesions were scored using a 4-point qualitative scale according to the degree of contrast enhancement at the CESM examination. The histological results were considered the gold standard. In the first analysis, enhancement degree scores of 2 and 3 were considered predictive of malignity. The sensitivity (SE) and positive predictive value (PPV) were significative lower for patients with lesions with microcalcifications without other radiological findings (SE = 53.3% vs. 82.2%, p-value < 0.001 and PPV = 84.2% vs. 95.2%, p-value = 0.049, respectively). On the contrary, the specificity (SP) and negative predictive value (NPV) were significative higher among lesions with microcalcifications without other radiological findings (SP = 95.8% vs. 84.2%, p-value = 0.026 and NPV = 82.9% vs. 55.2%, p-value < 0.001, respectively). In a second analysis, degree scores of 1, 2, and 3 were considered predictive of malignity. The SE (80.0% vs. 96.8%, p-value < 0.001) and PPV (70.6% vs. 88.3%, p-value: 0.005) were significantly lower among lesions with microcalcifications without other radiological findings, while the SP (85.9% vs. 50.9%, p-value < 0.001) was higher. The enhancement of microcalcifications has low sensitivity in predicting malignancy. However, in certain controversial cases, the absence of CESM enhancement due to its high negative predictive value can help to reduce the number of biopsies for benign lesions.

An Ultrasensitive miRNA-Based Genosensor for Detection of MicroRNA 21 in Gastric Cancer Cells Based on Functional Signal Amplifier and Synthesized Perovskite-Graphene Oxide and AuNPs

In the present research work, the state-of-art label-free electrochemical genosensing platform was developed based on the hybridization process in the presence of [Fe(CN)₆]^3-/4- as an efficient redox probe for sensitive recognition of the miRNA-21 in human gastric cell lines samples. To attain this aim, perovskite nanosheets were initially synthesized. Afterward, the obtained compound was combined with the graphene oxide resulting in an effective electrochemical modifier, which was dropped on the surface of the Au electrode. Then, AuNPs (Gold Nano Particles) have been electrochemically-immobilized on perovskite-graphene oxide/Au-modified electrode surface through the chronoamperometry (CA) technique. Finally, a self-assembling monolayer reaction of ss-capture RNA ensued by the thiol group at the end of the probe with AuNPs on the modified electrode surface. miRNA-21 has been cast on the Au electrode surface to apply the hybridization process. To find out the effectiveness of the synthesized modifier agent, the electrochemical behavior of the modified electrode has been analyzed through DPV (differential pulse voltammetry) and CV (cyclic voltammetry) techniques. The prepared biomarker-detection bioassay offers high sensitivity and specificity, good performance, and appropriate precision and accuracy for the highly-sensitive determination of miRNA-21. Different characterization methods have been used, such as XRD, Raman, EDS, and FE-SEM, for morphological characterization and investigation of particle size. Based on optimal conditions, the limit of detection and quantification have been acquired at 2.94 fM and 8.75 fM, respectively. Furthermore, it was possible to achieve a wide linear range which is between 10^-14 and 10^-7 for miRNA-21. Moreover, the selectivity of the proposed biosensing assay was investigated through its potential in the detection of one, two, and three-base mismatched sequences. Moreover, it was possible to investigate the repeatability and reproducibility of the related bio-assay. To evaluate the hybridization process, it is important that the planned biomarker detection bio-assay could be directly re-used and re-generated.

Bone Marrow Mesenchymal Stem Cell (BMSC)-Derived Exosomes Regulates Growth of Breast Cancer Cells Mediated by Hedgehog Signaling Pathway

BMSCs promote breast cancer development mainly through tumor microenvironment pathway and secreting exosomes. However, the mechanism is unclear. This study mainly explores whether BMSC-derived exosomes influence breast cancer by mediating Hedgehog signaling pathway. MCF-7 and BMSC were cultured and then assigned into MCF-7 +Vehicle group, MCF-7+ Exosome group, and MCF-7+Exosome+Gant61 (Hedgehog signaling blocker) group followed by analysis of cell proliferation and migration, p-Akt and β-catenin expression. MCF-7+Exosome group had the highest OD450 value compared to other two groups (P >0.05). In addition, migration distance of MCF-7 cells was the highest in MCF-7+Exosome group without difference between other two groups (P >0.05). Gli1 and SMO expression in MCF-7+Exosome group was highest compared to other two groups (P >0.05). In conclusion, exosome from BMSC promotes breast cancer cell proliferation and migration. The mechanism may be through raising GLI1, Smo protein expression, further raising the Hedgehog signaling pathway to some extent.

Salivary Metabolomics for Systemic Cancer Diagnosis: A Systematic Review

Cancers are the leading cause of death worldwide. The most common cancers include breast, lung, and colorectum. Salivary metabolome profiling is a novel non-invasive method in oncological diagnosis. This systematic review was designed to answer the question "Are salivary metabolites reliable for the diagnosis of systemic cancers?". Following the inclusion and exclusion criteria, nineteen studies were included (according to PRISMA statement guidelines). Changes in salivary metabolome were most commonly determined in patients with breast cancer, gastrointestinal cancers, and lung cancer. Most studies involved unstimulated whole saliva as the diagnostic material, evaluated by different spectroscopic methods. Among the found saliva metabolites, the alterations in the metabolic pathways of amino acids and polyamines were most frequently observed, which showed significant predictive values in oncological diagnostics. The most frequently encountered risks of bias were the absence of data regarding blinding, sample size justification, and randomisation. In conclusion, salivary metabolites seem to be potentially reliable for detecting the most common systemic cancers. However, further research is desirable to confirm these outcomes and to detect new potential metabolic biomarkers in saliva.

Dual-Channel Detection of Breast Cancer Biomarkers CA15-3 and CEA in Human Serum Using Dialysis-Silicon Nanowire Field Effect Transistor

BACKGROUND

Breast cancer (BC) is the most common malignant tumors and the leading cause of cancer deaths among women. The early diagnosis and treatment of BC are effective measures that can increase survival rates and reduce mortality. Carbohydrate antigens 15-3 (CA15-3) and carcinoma embryonic antigens (CEA) have been regarded as the most two valuable tumor markers of BC. The combined detection of CA15-3 and CEA could improve the sensitivity and accuracy of early diagnosis for BC.

METHODS

The multi-channel double-gate silicon nanowire field effect transistor (SiNW-FET) biosensors were fabricated by using the top-down semiconductor manufacturing technology. By surface modification of the different SiNW surfaces with monoclonal CA15-3 and CEA antibodies separately, the prepared SiNW-FET was processed into biosensor for dual-channel detection of CA15-3 and CEA.

RESULTS

The prepared SiNW-FET biosensors were proved to have high sensitivity and specificity for the dual-channel detection of CA15-3 and CEA, and the detection limit is as low as 0.1U/mL CA15-3 and 0.01 ng/mL CEA. Moreover, the SiNW-FET biosensors were able to detect CA15-3 and CEA in serum by connecting a miniature hemodialyzer.

CONCLUSION

The present study reported a SiNW-FET biosensor for dual-channel detection of breast cancer biomarkers CA15-3 and CEA in serum, which has potential clinical application value for the early diagnosis and curative effect observation of BC.

Identifying distinctive tissue and fecal microbial signatures and the tumor-promoting effects of deoxycholic acid on breast cancer

Introduction

A growing body of evidence indicates that the dysbiosis of both mammary and intestinal microbiota is associated with the initiation and progression of breast tumors. However, the microbial characteristics of patients with breast tumors vary widely across studies, and replicable biomarkers for early-stage breast tumor diagnosis remain elusive.

Methods

We demonstrate a machine learning-based method for the analysis of breast tissue and gut microbial differences among patients with benign breast disease, patients with breast cancer (BC), and healthy individuals using 16S rRNA sequence data retrieved from eight studies. QIIME 2.0 and R software (version 3.6.1) were used for consistent processing. A naive Bayes classifier was trained on the RDP v16 reference database to assign taxonomy using the Vsearch software.

Results

After re-analyzing with a total of 768 breast tissue samples and 1,311 fecal samples, we confirmed that Halomonas and Shewanella were the most representative genera of BC tissue. Bacteroides are frequently and significantly enriched in the intestines of patients with breast tumor. The areas under the curve (AUCs) of random forest models were 74.27% and 68.08% for breast carcinoma tissues and stool samples, respectively. The model was validated for effectiveness via cohort-to-cohort transfer (average AUC =0.65) and leave-one-cohort-out (average AUC = 0.66). The same BC-associated biomarker Clostridium_XlVa exists in the tissues and the gut. The results of the in-vitro experiments showed that the Clostridium-specific-related metabolite deoxycholic acid (DCA) promotes the proliferation of HER2-positive BC cells and stimulates G0/G1 phase cells to enter the S phase, which may be related to the activation of peptide-O-fucosyltransferase activity functions and the neuroactive ligand-receptor interaction pathway.

Discussion

The results of this study will improve our understanding of the microbial profile of breast tumors. Changes in the microbial population may be present in both the tissues and the gut of patients with BC, and specific markers could aid in the early diagnosis of BC. The findings from in-vitro experiments confirmed that Clostridium-specific metabolite DCA promotes the proliferation of BC cells. We propose the use of stool-based biomarkers in clinical application as a non-invasive and convenient diagnostic method.

Deep transformation models for functional outcome prediction after acute ischemic stroke

In many medical applications, interpretable models with high prediction performance are sought. Often, those models are required to handle semistructured data like tabular and image data. We show how to apply deep transformation models (DTMs) for distributional regression that fulfill these requirements. DTMs allow the data analyst to specify (deep) neural networks for different input modalities making them applicable to various research questions. Like statistical models, DTMs can provide interpretable effect estimates while achieving the state-of-the-art prediction performance of deep neural networks. In addition, the construction of ensembles of DTMs that retain model structure and interpretability allows quantifying epistemic and aleatoric uncertainty. In this study, we compare several DTMs, including baseline-adjusted models, trained on a semistructured data set of 407 stroke patients with the aim to predict ordinal functional outcome three months after stroke. We follow statistical principles of model-building to achieve an adequate trade-off between interpretability and flexibility while assessing the relative importance of the involved data modalities. We evaluate the models for an ordinal and dichotomized version of the outcome as used in clinical practice. We show that both tabular clinical and brain imaging data are useful for functional outcome prediction, whereas models based on tabular data only outperform those based on imaging data only. There is no substantial evidence for improved prediction when combining both data modalities. Overall, we highlight that DTMs provide a powerful, interpretable approach to analyzing semistructured data and that they have the potential to support clinical decision-making.

Peptidomimetics in cancer targeting

The low efficiency of treatment strategies is one of the main obstacles to developing cancer inhibitors. Up to now, various classes of therapeutics have been developed to inhibit cancer progression. Peptides due to their small size and easy production compared to proteins are highly regarded in designing cancer vaccines and oncogenic pathway inhibitors. Although peptides seem to be a suitable therapeutic option, their short lifespan, instability, and low binding affinity for their target have not been widely applicable against malignant tumors. Given the peptides' disadvantages, a new class of agents called peptidomimetic has been introduced. With advances in physical chemistry and biochemistry, as well as increased knowledge about biomolecule structures, it is now possible to chemically modify peptides to develop efficient peptidomimetics. In recent years, numerous studies have been performed to the evaluation of the effectiveness of peptidomimetics in inhibiting metastasis, angiogenesis, and cancerous cell growth. Here, we offer a comprehensive review of designed peptidomimetics to diagnose and treat cancer.

Multifunctional hybrid nanoparticles in diagnosis and therapy of breast cancer

Breast cancer is the most prevalent non-cutaneous malignancy in women, with greater than a million new cases every year. In the last decennium, numerous diagnostic and treatment approaches have been enormously studied for Breast cancer. Among the different approaches, nanotechnology has appeared as a promising approach in preclinical and clinical studies for early diagnosis of primary tumors and metastases and eradicating tumor cells. Each of these nanocarriers has its particular advantages and drawbacks. Combining two or more than two constituents in a single nanocarrier system leads to the generation of novel multifunctional Hybrid Nanocarriers with improved structural and biological properties. These novel Hybrid Nanocarriers have the capability to overcome the drawbacks of individual constituents while having the advantages of those components. Various hybrid nanocarriers such as lipid polymer hybrid nanoparticles, inorganic hybrid nanoparticles, metal-organic hybrid nanoparticles, and hybrid carbon nanocarriers are utilized for the diagnosis and treatment of various cancers. Certainly, Hybrid Nanocarriers have the capability to encapsulate multiple cargos, targeting agents, enhancement in encapsulation, stability, circulation time, and structural disintegration compared to non-hybrid nanocarriers. Many studies have been conducted to investigate the utilization of Hybrid nanocarriers in breast cancer for imaging platforms, photothermal and photodynamic therapy, chemotherapy, gene therapy, and combinational therapy. In this review, we mainly discussed in detailed about of preparation techniques and toxicological considerations of hybrid nanoparticles. This review also discussed the role of hybrid nanocarriers as a diagnostic and therapeutic agent for the treatment of breast cancer along with alternative treatment approaches apart from chemotherapy including photothermal and photodynamic therapy, gene therapy, and combinational therapy.

PRR11 in Malignancies: Biological Activities and Targeted Therapies

Proline rich 11 (PRR11), initially renowned for its relevance with cell-cycle progression, is a proline-rich protein coding gene in chromosome 17q22-23. Currently, accumulating studies have demonstrated that PRR11 plays a critical role in cellular proliferation, colony formation, migration, invasion, cell-cycle progression, apoptosis, autophagy and chemotherapy resistance via multiple signaling pathways and biological molecules in several solid tumors. In particular, PRR11 also serves as a promising prognostic indicator in a limited number of human cancers, gradually manifesting its potential application for targeted therapies. In this review, we summarize functional activities, related signaling pathways and biological molecules of PRR11 in various malignancies and generalize potential application of PRR11 for targeted therapies, thereby contributing to further exploration of PRR11 in cancer treatment.

Exploring EPR Parameters of 187Re Complexes for Designing New MRI Probes: From the Gas Phase to Solution and a Model Protein Environment

Breast cancer is one of the major types of cancer around the world, and early diagnosis is essential for successful treatment. New contrast agents (CAs), with reduced toxicology, are needed to improve diagnosis. One of the most promising Magnetic Resonance Imaging (MRI) CA is based on rhenium conjugated with a benzothiazole derivate (ReABT). In this sense, DFT has been used to evaluate the best methodology for calculating the hyperfine coupling constant (Aiso) of ReABT. Then, a thermodynamic analysis was performed to confirm the stability of the complex. Furthermore, a docking study of ReABT at the enzyme PI3K active site and Aiso calculations of ReABT in the enzyme environment were carried out. The best methodology for the Aiso calculation of ReABT was using the M06L functional, SARC-ZORA-TZVP (for Re) and TZVP (for all other atoms) basis set, relativistic Hamiltonian, and the CPCM solvation model with water as the solvent which confirm that the relativistic effects are important for calculating the Aiso values. In addition, thermodynamic analysis indicates that ReABT presents a higher stability and a lower toxicity than Gd-based CAs. The docking studies point out that ReABT interacts with amino acids residues of alanine, aspartate, and lysine from the PI3K active site. Considering the enzyme environment, Aiso values decrease significantly. These findings indicate that the CA candidate ReABT could be a good candidate for a new contrast agent.

Plasma Levels of CXC Motif Chemokine 1 (CXCL1) and Chemokine 8 (CXCL8) as Diagnostic Biomarkers in Luminal A and B Breast Cancer

Chemokines are involved in the regulation of immune balance and in triggering an immune response. CXCL1 and CXCL8 belong to the ELR-motif-containing group of CXC chemokines, which, in breast cancer (BC), stimulate angiogenesis and increase migration and invasiveness of tumor cells. The aim of this study was to evaluate CXCL1, CXCL8 and comparative marker CA 15-3 plasma concentrations in BC patients with luminal subtypes A and B. The study group consisted of 100 patients with BC, and the control group of 50 subjects with benign breast lesions and 50 healthy women. Chemokines concentrations were determined by ELISA method; CA15-3-by CMIA. Concentrations of CXCL8 and CA15-3 were significantly higher in BC total group and luminal B (for CA15-3 also in luminal A) subtype of BC than in healthy controls and subjects with benign lesions. In the total BC group, the highest SE, PPV and NPV were observed for CXCL8 (70%, 77.78%, 50%, resp.). A combined analysis of tested chemokines with CA 15-3 increased SE and NPV values (96%, 69.23%, resp.). The diagnostic power of the test (measured by area under ROC curve (AUC)) showed the highest value for CXCL8 in the total BC group (0.6410), luminal A (0.6120) and B subgroup of BC (0.6700). For the combined parameter, the AUC was increasing and reached the highest value for CXCL1 + CXCL8 + CA15-3 combination (0.7024). In light of these results, we suggest that CXCL8 could be used as an additional diagnostic marker that would positively influence the diagnostic utility of CA 15-3, especially in luminal B subtype of BC.

Effectiveness and Safety of Zercepac and Reference Trastuzumab in the Neoadjuvant Setting for Early-Stage Breast Cancer: A Retrospective Cohort Study

Aim

Since the high cost of reference trastuzumab limits its clinical application, this study aimed to compare the effectiveness and safety of the Zercepac and reference product trastuzumab in neoadjuvant therapy for HER2-positive breast cancer.

Methods

This study retrospectively collected clinical data of patients with early-stageHER2-positive breast cancer, who received trastuzumab, pertuzumab, docetaxel, and platinum as neoadjuvant therapy from November 2020 to July 2021. Patients were divided into the Zercepac and reference trastuzumab groups. Reduction in tumor size, clinical response based on RECIST1.1 criteria, pathological complete response (pCR), and adverse events (AEs) were evaluated. Multivariate logistic regression analyses were used to adjust confounders.

Results

A total of 105 patients were included in the study, among them, 65 were in the Zercepac group and 40 were in the reference trastuzumab group. The percentage of tumor shrinkage from baseline was comparable between the Zercepac and reference trastuzumab group (47.6 ± 18.6% vs. 43.0 ± 19.9%, p = 0.235). Clinical partial response rate was similar between the two groups (81.5% vs. 70.0%, p = 0.172). There were 28 cases of pCR (70.0%) in the reference trastuzumab group and 46 cases of pCR (70.8%) in the Zercepac group (p = 0.933). The choice of Zercepac or reference trastuzumab was not significantly associated with pCR (OR = 0.96, 95%CI: 0.41-2.28, p = 0.933). Adverse events (AEs) were observed in all patients, and the incidence of ≥3 grade AEs was comparable between the two groups (81.5% vs. 70.0%, p = 0.172).

Conclusion

Zercepac has similar effectiveness and safety profile compared with reference trastuzumab in neoadjuvant therapy, which provides treatment options for patients with HER2-positive breast cancer.

Correlation of CT-data derived from multiparametric dual-layer CT-maps with immunohistochemical biomarkers in invasive breast carcinomas

OBJECTIVE

To examine the correlation of quantitative measurements from material decomposition maps calculated from dual-layer CT (DLCT)-image datasets with immunohistochemical biomarkers of invasive breast carcinomas.

MATERIAL AND METHODS

All patients at the University Breast Cancer Center who underwent a clinically indicated dual-layer CT-scan for staging of invasive ductal breast carcinoma from 01/2016 to 07/2020 were prospectively included. Iodine concentration maps and maps of the effective atomic numbers (Zeffective) were reconstructed from the image datasets. ROI-based evaluations of the index tumors and predefined references tissues for normalization were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Statistical analysis was essentially descriptive using Spearmańs rank correlation and (multivariable) partial correlation.

RESULTS

Bivariate showed statistically significant correlations of iodine contents (r = -0.154/-0.202/0.180, p = 0.039/0.006/0.015), and Zeffective-values (r = -0.158/-0.199/0.179, p = 0.034/0.007/0.016) for all 184 carcinomas and the subgroup of 168 invasive ductal carcinomas. The results were confirmed by multivariate analyses with "age", "diameter" and "ACR-grade" as possible confounders. Normalization of the measured target values with those in the aorta confirmed significant correlations of iodine content and Zeffective compared to Estrogen (r = 0.174, p = 0.019), Progesteron (r = 0.168/0.177, p = 0.024/0.017), and HER2 receptor expression (r = -0.222/-0.184, p = 0.003/0.013). All CT-parameters showed significant correlations with immunohistochemical subtyping (r = 0.191/0.192, p = 0.010).

CONCLUSIONS

Our preliminary results indicate that iodine content and Zeffective-values derived from DLCT-examinations correlate with hormone receptor expression in invasive breast carcinomas. Assignments to benign entities already seam feasible in clinical routine CT-diagnostics. After further investigations iodine content and Zeffective may be translated as diagnostical and prognostical biomarkers into clinical routine in the long term.

Relationship between Baseline [18F]FDG PET/CT Semiquantitative Parameters and BRCA Mutational Status and Their Prognostic Role in Patients with Invasive Ductal Breast Carcinoma

AIM

To assess the relationship between [¹⁸F]FDG PET/CT, breast cancer gene (BRCA) status, and their prognostic role in patients with ductal breast cancer (DBC).

METHODS

Forty-one women were included. PET/CT semiquantitative parameters such as standardized uptake value (SUV) body weight max (SUVmax), SUV body weight mean (SUVmean), SUV lean body mass (SUVlbm), SUV body surface area (SUVbsa), metabolic tumor volume (MTV), total lesion glycolysis (TLG), ratio SUVmax/blood-pool (S-BP), and ratio SUVmax/liver (S-L) were also extracted. The relationship between these parameters, BRCA, and other clinicopathological features were evaluated. Kaplan-Meier, univariate, and multivariate analyses were performed to find independent prognosticators for progression free (PFS) and overall survival (OS).

RESULTS

Significant positive correlations between BRCA status and SUVmax (p-value 0.025), SUVlbm (p-value 0.016), and SUVbsa (p-value 0.018) were reported. Mean PFS was 53.90 months with relapse/progression of disease occurring in nine (22.0%) patients; mean OS was 57.48 months with death occurring in two (4.9%) patients. Survival curves revealed TLG, MTV, and BRCA status as prognosticator for PFS; BRCA was also a prognosticator for OS. Univariate and multivariate analyses did not confirm such insights.

CONCLUSION

We reported a correlation between some PET/CT parameters and BRCA status; some insights on their prognostic role have been underlined.

Label-Free Surface Enhanced Raman Spectroscopy for Cancer Detection

Simple Summary

Blood is considered a rich reservoir of biomarkers for disease diagnosis. Surface-enhanced Raman scattering (SERS) is known for its high sensitivity and has been successfully employed to differentiate blood samples from cancer patients versus healthy individuals. Different from previous reports, this study aims at investigating the reliability of the observed results by varying several parameters influencing the observed spectra. Thus, blood taken from 30 healthy individuals as the control group, 30 patients with different types of cancers, and 15 patients with various types of chronic diseases were used in the study. The results revealed that spectral differences in the cancer group was directly related to the presence of cancer-related biomarkers. Although data were obtained from only small group of patients, the recorded sensitivity and specificity values clearly show the power of the technique to detect cancer.

Abstract

Blood is a vital reservoir housing numerous disease-related metabolites and cellular components. Thus, it is also of interest for cancer diagnosis. Surface-enhanced Raman spectroscopy (SERS) is widely used for molecular detection due to its very high sensitivity and multiplexing properties. Its real potential for cancer diagnosis is not yet clear. In this study, using silver nanoparticles (AgNPs) as substrates, a number of experimental parameters and scenarios were tested to disclose the potential for this technique for cancer diagnosis. The discrimination of serum samples from cancer patients, healthy individuals and patients with chronic diseases was successfully demonstrated with over 90% diagnostic accuracies. Moreover, the SERS spectra of the blood serum samples obtained from cancer patients before and after tumor removal were compared. It was found that the spectral pattern for serum from cancer patients evolved into the spectral pattern observed with serum from healthy individuals after the removal of tumors. The data strongly suggests that the technique has a tremendous potential for cancer detection and screening bringing the possibility of early detection onto the table.

RhoBTB3 Regulates Proliferation and Invasion of Breast Cancer Cells via Col1a1

Breast cancer is the leading cause of cancer-related death in women worldwide, despite medical and technological advancements. The RhoBTB family consists of three isoforms: RhoBTB1, RhoBTB2, and RhoBTB3. RhoBTB1 and RhoBTB2 have been proposed as tumor suppressors in breast cancer. However, the roles of RhoBTB3 proteins are unknown in breast cancer. Bioinformatics analysis, including Oncomine, cBioportal, was used to evaluate the potential functions and prognostic values of RhoBTB3 and Col1a1 in breast cancer. qRT-PCR analysis and immunoblotting assay were performed to investigate relevant expression. Functional experiments including proliferation assay, invasion assay, and flow cytometry assay were conducted to determine the role of RhoBTB3 and Col1a1 in breast cancer cells. RhoBTB3 mRNA levels were significantly up-regulated in breast cancer tissues as compared to in adjacent normal tissues. Moreover, RhoBTB3 expression was found to be associated with Col1a1 expression. Decreasing RhoBTB3 expression may lead to decreases in the proliferative and invasive properties of breast cancer cells. Further, Col1a1 knockdown in breast cancer cells limited the proliferative and invasive ability of cancer cells. Knockdown of RhoBTB3 may exert inhibit the proliferation, migration, and metastasis of breast cancer cells by repressing the expression of Col1a1, providing a novel therapeutic strategy for treating breast cancer.

Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) about 22 nucleotides in size, which play an important role in gene regulation and are involved in almost all major cellular physiological processes. In recent years, the abnormal expression of miRNAs has been shown to be associated with human diseases including cancer. In the past ten years, the link between miRNAs and various cancers has been extensively studied, and the abnormal expression of miRNAs has been reported in various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, liver cancer, breast cancer, and prostate cancer. Due to the high malignancy grade of these cancers, it is more necessary to develop the related diagnostic and prognostic methods. According to the study of miRNAs, many potential cancer biomarkers have been proposed for the diagnosis and prognosis of diseases, especially cancer, thus providing a new theoretical basis and perspective for cancer screening. The use of miRNAs as biomarkers for diagnosis or prognosis of cancer has the advantages of being less invasive to patients, with better accuracy and lower price. In view of the important clinical significance of miRNAs in human cancer research, this article reviewed the research status of miRNAs in the above-mentioned cancers in 2021, especially in terms of diagnosis and prognosis, and provided some new perspectives and theoretical basis for the diagnosis and treatment of cancers.

Comparison of Efficacy and Psychology of Breast-Conserving Surgery and Modified Radical Mastectomy on Patients with Early Breast Cancer under Graded Nursing

Objective

To compare the efficacy and psychology of breast-conserving surgery and modified radical mastectomy in patients with early breast cancer (BC) under graded nursing.

Methods

Forty-one early breast-conserving surgery BC patients admitted to our hospital from April 2020 to March 2022 were regarded as group A, and 52 with modified radical surgery were seen as group B. The operating time, intraoperative bleeding, postoperative drainage, and hospital stay were compared, and the postoperative adverse effects were counted. In addition, patients' psychology and quality of life were assessed using the HAMD, HAMA, and QLSBC rating scales. At the time of discharge, a treatment satisfaction survey was conducted.

Results

The operative time, intraoperative bleeding, postoperative drainage, and hospital stay of patients in group A were lower than those in group B (P < 0.05). After treatment, the HAMD and HAMA scores were lower in group A than in group B, while the QLSBC scores and treatment satisfaction were higher (P < 0.05).

Conclusion

Breast-conserving surgery under graded nursing is less damaging to early BC patients. It can effectively shorten the postoperative recovery process and improve the psychology and quality of life, so it has higher clinical applicability.

Clinical significance for diagnosis and prognosis of POP1 and its potential role in breast cancer: a comprehensive analysis based on multiple databases

Background: Breast cancer (BC) is one of the most common cancers in women. The discovery of available biomarkers is crucial for early diagnosis and improving prognosis. The effect of POP1 in BC remains unrevealed. Our study aims to explore the expression of POP1 in BC and demonstrate its clinical significance and potential molecular mechanisms.

Methods: The Cancer Genome Atlas (TCGA) BC cohort transcriptome data and corresponding clinical information were downloaded. GSE42568 cohort, GSE162228 cohort, GSE7904 cohort, and GSE161533 cohort in the Gene Expression Omnibus (GEO) database were used as verification groups. R software and several web tools were used for statistical analysis. Moreover, the proliferation, transwell, wound healing experiments, and flow cytometry were used for in vitro investigation.

Results: Compared with normal breast tissue, POP1 expression was up-regulated in BC tissue with a higher mutation rate. POP1 had good diagnostic value for BC and could be utilized as a new marker. POP1 was significantly correlated with multiple pathways in BC and played an important role in the immune infiltration of BC. High-POP1 expression patients were more prone to be responded to immunotherapy and had a significantly higher percentage of immunotherapy response rate. Moreover, POP1 promoted proliferation and migration and inhibited apoptosis in BC cells.

Conclusions: POP1 expression was up-regulated in BC and was associated with a poor prognosis. Patients with high-POP1 expression were more likely to be responded to immunotherapy. Our study can provide a potential marker POP1 for BC, which is beneficial in the diagnosis and treatment of BC.

Whole-genome circulating tumor DNA methylation landscape reveals sensitive biomarkers of breast cancer

The changes in circulating tumor DNA (ctDNA) methylation are believed to be early events in breast cancer initiation, which makes them suitable as promising biomarkers for early diagnosis. However, applying ctDNA in breast cancer early diagnosis remains highly challenging due to the contamination of background DNA from blood and low DNA methylation signals. Here, we report an improved way to extract ctDNA, reduce background contamination, and build a whole‐genome bisulfite sequencing (WGBS) library from different stages of breast cancer. We first compared the DNA methylation data of 74 breast cancer patients with those of seven normal controls to screen candidate methylation CpG site biomarkers for breast cancer diagnosis. The obtained 26 candidate ctDNA methylation biomarkers produced high accuracy in breast cancer patients (area under the curve [AUC] = 0.889; sensitivity: 100%; specificity: 75%). Furthermore, we revealed potential ctDNA methylated CpG sites for detecting early‐stage breast cancer (AUC = 0.783; sensitivity: 93.44%; specificity: 50%). In addition, different subtypes of breast cancer could be well distinguished by the ctDNA methylome, which was obtained through our improved ctDNA‐WGBS method. Overall, we identified high specificity and sensitivity breast cancer‐specific methylation CpG site biomarkers, and they will be expected to have the potential to be translated to clinical practice.

Atractylenolide I Inhibits Triple-Negative Breast Cancer Cell Proliferation and Promotes Apoptosis via Blocking the Janus Kinase 2/Signal Transducer and Activator of Transcription 3 Signaling Pathway

Bioactive agent Atractylenolide I (AT-1) has been shown to possess therapeutic value for treating various malignancies. The purpose of the current study is to clarify the potential effect of AT-1 on the development of triple-negative breast cancer (TNBC) and to investigate relevant signaling pathways involved in its mechanism. MTT assay was used to assess the effect of different concentrations of AT-1 on cell survival rate in MCF-10A normal breast epithelial cell line and MDA-MB-231 TNBC cell line. Exogenous IL-6 and WP1066 respectively acted as the agonist and the inhibitor of JAK2/STAT3. Determination of MDA-MB-231 cell viability, proliferation and apoptosis employed MTT, colony formation assay and TUNEL. Western blotting was conducted to measure the expression of proliferation- and apoptosis-related proteins. The viability of MCF-10A cells was unaffected by AT-1, whereas in MDA-MB-231 cells the proliferation level was decreased and the apoptosis level was increased after AT-1 treatment. IL-6 partially restored the expression of AT-1-blocked JAK2/STAT3, and WP1066 inhibited JAK2/STAT3 expression in combination with IL-6 and AT-1. Furthermore, compared with the AT-1 group, co-incubation of IL-6 and AT-1 partially restored the proliferative capacity and reduced the apoptosis of MDA-MB-231 cells, while WP1066 reversed these effects in combination with IL-6 and AT-1. AT-1 suppressed proliferation and promoted apoptosis in TNBC cells likely through inhibiting the activation of JAK2/STAT3 signaling pathway. The findings from this study may provide guidance for future studies on AT-1 and theoretical basis of AT-1 pharmacological activities.

Advances in nano-based materials for glioblastoma multiforme diagnosis: A mini-review

The development of nano-based materials for diagnosis enables a more precise prognosis and results. Inorganic, organic, or hybrid nanoparticles using nanomaterials, such as quantum dots, extracellular vesicle systems, and others, with different molecular compositions, have been extensively explored as a better strategy to overcome the blood-brain barrier and target brain tissue and tumors. Glioblastoma multiforme (GBM) is the most common and aggressive primary tumor of the central nervous system, with a short, established prognosis. The delay in early detection is considered a key challenge in designing a precise and efficient treatment with the most encouraging prognosis. Therefore, the present mini-review focuses on discussing distinct strategies presented recently in the literature regarding nanostructures’ use, design, and application for GBM diagnosis.

Lipid-coated bismuth nanoflower as the thermos-radio sensiti for therapy of lung metastatic breast cancer: Preparation, optimisation, and characterisation

Lung metastatic breast cancer (LMBC) leads to a large number of deaths in women with breast cancer, and radiotherapy has been considered the common assay for tumour therapy except for surgery. However, radiotherapy still faces problems of low efficiency due to resistance and easily induced side effects. Here, the authors designed lipid-decorated bismuth-based nanoflowers (DP-BNFs) as both a radiosensitiser and a photothermal therapy agent for LMBC treatment. The BNFs were prepared by oxidation of bismuth nitrate and subsequent reduction using sodium borohydride. The preparation parameters and formulation of DP-BNFs were optimised via a single-factor experiment, with the factors including reaction temperature, a molar ratio of reducing agents, and the types and amount of decorated lipid materials. The result indicated that the BNFs prepared at 170°C with the Bi/NaBH₄ ratio of 1:0.7 exhibited the best yield and particle size around 160 nm. After being spray dried with lactose to prepare dry powder inhalation (DP-BNF@Lat-MPs), their effects on improving therapeutic efficiency of the radiotherapy and photothermal therapy combination were measured using the western blot assay to determine the tumour apoptosis. In a word, DP-BNF@Lat-MPs could be a novel inhalable integrated microsphere that provides a new possibility for thermoradiotherapy of LMBC.

Determination of adenosine and its modifications in urine and plasma from breast cancer patients by hydrophilic interaction liquid chromatography-tandem mass spectrometry

RNA modifications have been revealed to be essential in many biological activities, and their disorders are associated with various human diseases, including cancers. 2'-O-methyladenosine (A_m), N¹-methyladenosine (m¹A), N⁶-methyladenosine (m⁶A), N⁶,2'-O-dimethyladenosine (m⁶A_m) and N⁶,N⁶-dimethyladenosine (m⁶₂A) are important adenosine (A) modifications. The noninvasive collection of urine samples and the diverse contents of metabolites in plasma make them favored biofluids for biomarkers discovery. In this work, we established a hydrophilic interaction liquid chromatography-tandem mass spectrometry (HILIC-MS/MS) method to quantify these six nucleosides in urine and plasma of healthy controls and breast cancer (BC) patients. The limit of detection (LOD) for A, A_m, m¹A, m⁶A, m⁶A_m, and m⁶₂A were 0.0025, 0.01, 0.05, 0.005, 0.005, and 0.005 nM. The results showed that the concentrations of A_m, m⁶A, and m⁶A_m were increased, whereas m¹A was decreased in the urine of BC patients compared with the healthy controls. We also found that the level ratios of m¹A/A, m⁶A/A, and m⁶A_m/A were all reduced in plasma from BC patients, compared with healthy controls. Interestingly, these ratios of methylated adenosine nucleosides to adenosine in plasma could better discriminate BC patients from healthy controls, compared to the levels of these nucleosides. The present study not only suggests these modified adenosines can act as noninvasive biomarkers of BC but also will contribute to investigating the impacts of RNA methylation on the occurrence and development of BC.

Quantification of Serum Exosome Biomarkers Using 3D Nanoporous Gold and Spectrophotometry

Tumor-derived exosomes may provide biomarkers for cancer treatment. Using sputtering technology, an affinity-based device to capture exosomes was developed using nanoporous substrate (NPG)-coated silicon microscopy. Immunology-based techniques detect and purify exosomes using gold coating with a specific antigen. Inverted fluorescent microscopy was used to detect target exosomes quantitatively utilizing fluorescent nanospheres as the label. We quantified the expression of CD63 surface protein markers on exosomes from conditioned culture media of breast cancer cells. The exosomes that targeted specific proteins with controls were statistically analyzed and compared to those that targeted non-specific proteins. Results from SEM showed that the exosomes were circular, between 30 and 150 nanometers in size. The porous gold substrates captured more exosomes than the nonporous substrates. Nitric acid treatments at different times resulted in a variety of pore sizes. Despite the increase in the size of the pores, the number of exosomes found in the porous gold substrate treated for 10 min nearly doubled compared to the one treated for 5 min. In this work, a fluorescence biosensor was developed to detect breast cancer exosomes using nanoporous gold substrates (NPG). Assay and model exosomes of specific breast cancer cells showed that exosomes exhibit diagnostic surface protein markers, reflecting the protein profile of their parent cells. Furthermore, the specific binding between the exosome surface antibodies and the targets identified the CD63 biomarkers on the exosome, suggesting these markers' diagnostic potential. This study can accelerate exosome research in determining tumor-related exosomes and develop novel cancer diagnostic methods.

Alternating exosomes and their mimetics as an emergent strategy for targeted cancer therapy

Exosomes, a subtype of the class of extracellular vesicles and nano-sized particles, have a specific membrane structure that makes them an alternative proposition to combat with cancer through slight modification. As constituents of all most all the primary body fluids, exosomes establish the status of intercellular communication. Exosomes have specific proteins/mRNAs and miRNAs which serve as biomarkers, imparting a prognostic tool in clinical and disease pathologies. They have efficient intrinsic targeting potential and efficacy. Engineered exosomes are employed to deliver therapeutic cargos to the targeted tumor cell or the recipient. Exosomes from cancer cells bring about changes in fibroblast via TGFβ/Smad pathway, augmenting the tumor growth. These extracellular vesicles are multidimensional in terms of the functions that they perform. We herein discuss the uptake and biogenesis of exosomes, their role in various facets of cancer studies, cell-to-cell communication and modification for therapeutic and diagnostic use.

Study on the Expression of lncRNA ATB and Nek9 in Breast Cancer Patients Based on Q-PCR Technology and Its Relationship with the Disease

To reveal the relationship between the expression and disease progression, the expression of long noncoding RNA ATB (lncRNA ATB) and related protein kinase 9 (Nek 9) in serum of breast cancer patients by real-time fluorescence quantitative PCR (Q-PCR) is analyzed. The patients treated in our hospital from April 2021 to February 2022 are selected and grouped into several groups. Among them, 73 patients diagnosed with breast cancer and 44 patients with benign breast disease are divided into groups A and B, respectively. In addition, 50 healthy subjects are chosen for group C. The expressions of lncRNA ATB and Nek9 in serum of patients are detected by Q-PCR, and the relationship between different pathological parameters and lncRNA ATB and Nek9 in group A is analyzed. Spearman correlation coefficient is used to evaluate the correlation between lncRNA ATB and Nek9 and disease. The experimental results show that lncRNA ATB and Nek9 in 3 groups are significantly different, and group A> group B> group C (all P < 0.05). The expression of lncRNA ATB and Nek9 is closely associated with lymph node metastasis and TNM stage in breast cancer patients (P < 0.05). Besides, the Spearman correlation coefficient shows that lncRNA ATB and Nek9 are positively correlated with breast cancer incidence (P < 0.05). It is evident that lncRNA ATB and Nek9 are expressed at high levels in breast cancer patients and are positively correlated with the occurrence and development of the disease.

Molecular Characterization of Exosomes for Subtype-Based Diagnosis of Breast Cancer

Breast cancer is very heterogeneous and the most frequently diagnosed cancer worldwide, and precise therapy targeting specific subtypes may improve the survival rates of breast cancer patients. In this study, we designed a biomimetic vesicle by camouflaging catalytic DNA machinery with a breast cancer cell membrane, which enabled the molecular classification of circulating exosomes for subtype-based diagnosis through homotypic recognition. In addition, the vesicles specifically targeted and fused with breast cancer exosomes with phenotypic homology and manipulated the DNA machinery to amplify electrochemical signaling using exosomal RNA as an endogenous trigger. The biomimetic vesicles prepared with MCF-7 cancer cell-derived membranes were shown to recognize estrogen receptor-positive breast cancer exosomes and exhibited a low detection limit of 557 particles mL^-1 with microRNA-375 used as the endogenous biomarker. Furthermore, the biomimetic vesicles prepared with MDA-MB-231 cancer cell-derived membranes displayed satisfactory performance in a homotypic analysis of triple-negative breast cancer exosomes with a potential therapeutic target, PD-L1 mRNA, used as the endogenous biomarker. Most importantly, cross-validation experiments confirmed the high accuracy and selectivity of this homotypic recognition-driven analysis for molecular subtyping of breast cancer. When applied to clinical samples of breast cancer patients, the vesicles demonstrated feasibility and reliability for evaluating the molecular features of cancer cell-derived exosomes and enabled stage-specific monitoring of breast cancer patients because the electrochemical signals showed a positive correlation with disease progression. Therefore, this work may provide new ideas for the precise diagnosis and personalized treatment of breast cancer patients throughout the whole disease process.

Early Predictive Value of NT-proBNP Combined With Echocardiography in Anthracyclines Induced Cardiotoxicity

Objective

Determine the predictive value of N-terminal pro-B-type natriuretic peptide (NT-proBNP) combined with echocardiography in the diagnosis of anthracyclines-induced chronic cardiotoxicity.

Methods

A total of 80 female breast cancer patients from January 2019 to October 2021 were included in our hospital. Twenty-six patients with cardiotoxicity were divided into the cardiac impairment group, and the 54 patients without cardiotoxicity were classified into the normal control group. NT-proBNP levels and cardiac echocardiography were measured before the start of the chemotherapy cycle, in cycle 3 of the chemotherapy, and after the chemotherapy cycle in all patients.

Results

After three cycles of chemotherapy and chemotherapy, the levels of NT-proBNP in patients of the two groups were significantly higher than those before chemotherapy (P < 0.05). The levels of NT-proBNP in the cardiac injury group after three cycles of chemotherapy and chemotherapy were higher than those in the normal control group at the same time point (P < 0.05). The LVEF of patients in the cardiac impairment group after chemotherapy was lower than that before chemotherapy, and the LVEF after chemotherapy was lower than that in the normal control group (P < 0.05). NT-proBNP had a negative correlation with LVEF (r = −0.549, P < 0.001). The AUC of NT-proBNP in combination with LVEF for predicting cardiotoxicity in our patient was 0.898(95%CI:0.829–0.966).

Conclusion

NT-proBNP combined with echocardiography has clinical significance in the detection of anthracyclines-induced cardiotoxicity, and it can detect early myocardial injury induced by anthracyclines, with early prediction value. It is important to protect heart function and judge prognosis.

Co-expression of DDR2 and IFITM1 promotes breast cancer cell proliferation, migration and invasion and inhibits apoptosis

PURPOSE

To investigate the roles of DDR2 and IFITM1 in breast cancer (BC).

METHODS

The expression of DDR2 and IFITM1 in BC tissues and cell lines was measured. DDR2 and/or IFITM1 were knocked down in BT20 and MDA-MB-231 cells, after which the viability, mobility and apoptosis of the cells were tested. Xenograft mouse models were established through subcutaneous tumor transplantation.

RESULTS

DDR2 and IFITM1 were highly expressed in invasive BC tissues and cell lines. Overexpression of DDR2 and/or IFITM1 was associated with poorer clinical outcomes and patient survival. Knockdown of DDR2 or IFITM1 suppressed the viability and invasiveness of BT20 and MDA-MB-231 cells and restrained the growth of xenograft tumors in nude mice. Simultaneous knockdown of IFITM1 and DDR2 surpassed knockdown of IFITM1 alone in suppressing BC development.

CONCLUSIONS

DDR2 and IFITM1 are co-expressed to facilitate the malignant behaviors of BC cells and promote the development of tumors.

Breast Cancer Classification Using FCN and Beta Wavelet Autoencoder

In this paper, a new classification approach of breast cancer based on Fully Convolutional Networks (FCNs) and Beta Wavelet Autoencoder (BWAE) is presented. FCN, as a powerful image segmentation model, is used to extract the relevant information from mammography images. It will identify the relevant zones to model while WAE is used to model the extracted information for these zones. In fact, WAE has proven its superiority to the majority of the features extraction approaches. The fusion of these two techniques have improved the feature extraction phase and this by keeping and modeling only the relevant and useful features for the identification and description of breast masses. The experimental results showed the effectiveness of our proposed method which has given very encouraging results in comparison with the states of the art approaches on the same mammographic image base. A precision rate of 94% for benign and 93% for malignant was achieved with a recall rate of 92% for benign and 95% for malignant. For the normal case, we were able to reach a rate of 100%.

Breast Cancer—How Can Imaging Help?

Breast cancer is the most common malignant disease among women, causing death and suffering worldwide. It is known that, for the improvement of the survival rate and the psychological impact it has on patients, early detection is crucial. For this to happen, the imaging techniques should be used at their full potential. We selected and examined 44 articles that had as subject the use of a specific imaging method in breast cancer management (mammography, ultrasound, MRI, ultrasound-guided biopsy, PET-CT). After analyzing their data, we summarized and concluded which are the best ways to use each one of the mentioned techniques for a good outcome. We created a simplified algorithm with easy steps that can be followed by radiologists when facing this type of neoplasia.

Classifying Breast Density from Mammogram with Pretrained CNNs and Weighted Average Ensembles

We are currently experiencing a revolution in data production and artificial intelligence (AI) applications. Data are produced much faster than they can be consumed. Thus, there is an urgent need to develop AI algorithms for all aspects of modern life. Furthermore, the medical field is a fertile field in which to apply AI techniques. Breast cancer is one of the most common cancers and a leading cause of death around the world. Early detection is critical to treating the disease effectively. Breast density plays a significant role in determining the likelihood and risk of breast cancer. Breast density describes the amount of fibrous and glandular tissue compared with the amount of fatty tissue in the breast. Breast density is categorized using a system called the ACR BI-RADS. The ACR assigns breast density to one of four classes. In class A, breasts are almost entirely fatty. In class B, scattered areas of fibroglandular density appear in the breasts. In class C, the breasts are heterogeneously dense. In class D, the breasts are extremely dense. This paper applies pre-trained Convolutional Neural Network (CNN) on a local mammogram dataset to classify breast density. Several transfer learning models were tested on a dataset consisting of more than 800 mammogram screenings from King Abdulaziz Medical City (KAMC). Inception V3, EfficientNet 2B0, and Xception gave the highest accuracy for both four- and two-class classification. To enhance the accuracy of density classification, we applied weighted average ensembles, and performance was visibly improved. The overall accuracy of ACR classification with weighted average ensembles was 78.11%.

Insights into the value of statistical models, solvent, and relativistic effects for investigating Re complexes of 2-(4'-aminophenyl)benzothiazole: a potential spectroscopic probe

Cancer affects a major part of the worldwide population, and, to minimize deaths, the diagnosis in the early stages of the disease is fundamental. Thus, to improve diagnosis and treatment new potential spectroscopic probes are crucial. Benzothiazole derivates present antitumor properties and are highly selective and interact strongly with the enzyme phosphoinositide 3-kinase (PI3K), which was associated with cell proliferation and breast cancer cells. In this paper, the rhenium shielding tensors (¹⁸⁷Re(σ)) and hydrogen and carbon chemical shifts (¹H(δ) and ¹³C(δ)) of the Re(CO)₃(NNO) complex conjugated with 2-(4'-aminophenyl)benzothiazole (ReABT) were evaluated. A statistical HCA model was used to analyze the best DFT protocol to compute σ and δ values and to evaluate the relativistic effects, both in the basis set and Hamiltonian as well as the functionals M06L or PBE0. The best protocol was applied to obtain ¹⁸⁷Re(σ) of the ReABT complex in different environments (gas phase, solution, and in the active site of the PI3K enzyme). The results point out that ¹⁸⁷Re(σ) values of the ReABT complex change significantly when the complex is docked in the PI3K enzyme.

Low CRIM1 Levels Predict Poor Prognosis in Breast Cancer Patients

Background

CRIM1 is involved in the development and preservation of the nervous system, capillary development, and vascular maintenance. Although CRIM1 was reported to involve in multiple cancers, its role in breast cancer is unclear.

Methods

We investigated CRIM1 expression levels using Oncomine, HPA, and immunohistochemistry analyses. BC-GenExMiner was employed to evaluate the relationship of CRIM1 expression with the clinicopathological characteristics of breast cancer. Its association with breast cancer prognosis was assessed by Kaplan-Meier analysis and PrognoScan. The correlation of the expression of CRIM1 with tumor immune infiltration was explored via TIMER. Gene set enrichment analysis (GSEA) was utilized to determine the cascades that are linked to CRIM1 in breast cancer. Finally, we explored CRIM1 and its co-expressed genes using R (3.6.3).

Results

Here, we find that CRIM1 expression was downregulated in various subtypes of breast cancer, and it was lowest in triple-negative breast cancers. ER and PR status were positively correlated with CRIM1 expression, while HER-2 expression was negatively correlated with CRIM1 expression. But in our immunohistochemical results in breast cancer specimens collected from our laboratory, HER-2 expression was positively correlated with CRIM1 expression. The expression of CRIM1 was correlated with menopause status, T stage, pathologic stage, histological type, and P53 status but not with age, N-stage, M-stage, Radiation therapy, and BRCA1/2 status. Survival analysis found that low CRIM1 expression was correlated with poorer DMFS, RFS and OS. Notably, CRIM1 expression was positively linked to the level of infiltration by CD8+ T-cells, endothelial cells, and neutrophils, and negatively linked to NK, B-cells, CD4+ T-cells, tumor purity, macrophage M1, and Tregs. Besides, DIXDC1 and PFDN6 were correlated to CRIM1 possibly.

Conclusion

Our findings demonstrated that low CRIM1 expression predict poor prognosis of breast cancer and CRIM1 might be used as a possible treatment target or prognostic marker in breast cancer. More researches are needed to better understand the prognostic value of CRIM1 in breast cancer.