Liquid biopsy and multiparametric analysis in management of liver malignancies: new concepts of the patient stratification and prognostic approach

Heat shock proteins in cancer - Known but always being rediscovered: Their perspectives in cancer immunotherapy

Heat shock proteins (HSPs) represent cellular chaperones that are classified into several families, including HSP27, HSP40, HSP60, HSP70, and HSP90. The role of HSPs in the cell includes the facilitation of protein folding and maintaining protein structure. Both processes play crucial roles during stress conditions in the cell such as heat shock, degradation, and hypoxia. Moreover, HSPs are important modulators of cellular proliferation and differentiation, and are strongly associated with the molecular orchestration of carcinogenesis. The expression and/or activity of HSPs in cancer cells is generally abnormally high and is associated with increased metastatic potential and activity of cancer stem cells, more pronounced angiogenesis, downregulated apoptosis, and the resistance to anticancer therapy in many patients. Based on the mentioned reasons, HSPs have strong potential as valid diagnostic, prognostic, and therapeutic biomarkers in clinical oncology. In addition, numerous papers describe the role of HSPs as chaperones in the regulation of immune responses inside and outside the cell. Importantly, highly expressed/activated HSPs may be inhibited via immunotherapeutic targets in various types of cancers. The aim of this work is to provide a comprehensive overview of the relationship between HSPs and the tumor cell with the intention of highlighting the potential use of HSPs in personalized cancer management.

Diagnostic Value of Multislice Spiral Computed Tomography Combined with Serum AFP, TSGF, and GP73 Assay in the Diagnosis of Primary Liver Cancer

Objective

To explore the diagnostic value of multislice spiral computed tomography (MSCT) scan combined with serum alpha-fetoprotein (AFP), tumor-specific growth factor (TSGF), and Golgi protein73 (GP73) assays in the diagnosis of primary liver cancer (PLC).

Methods

Totally, 60 patients with PLC admitted to The Second Hospital of Dalian Medical University from January 2019 to January 2020 were included in group A, 60 patients with liver cirrhosis were included in group B, and 60 healthy subjects were included in group C. The serum AFP, TSGF, and GP73 levels were determined, and all participants received MSCT scanning. The diagnostic efficacy of MSCT, assays of serum AFP, TSGF, and GP73, and their combined detection was analyzed.

Results

Group A had the highest levels of AFP, TSGF, and GP73, followed by group B, and then group C. The sensitivity, specificity, positive predictive value, and negative predictive value of MSCT for PLC were 80.0%,91.7%, 82.8%, and 90.2%, respectively, while those of combined detection of MSCT plus serum AFP, TSGF, and GP73 for PLC were 100.0%, 93.3%, 88.2%, and 100.0%. The combined detection was associated with significantly a higher detection rate of PLC versus stand-alone detection.

Conclusion

MSCT plus serum AFP, TSGF, and GP73 has a higher detection rate versus stand-alone detection, which shows great potential in the diagnosis of PLC.

Human disease biomarker panels through systems biology

As more uses for biomarkers are sought after for an increasing number of disease targets, single-target biomarkers are slowly giving way for biomarker panels. These panels incorporate various sources of biomolecular and clinical data to guarantee a higher robustness and power of separation for a clinical test. Multifactorial diseases such as psychiatric disorders show great potential for clinical use, assisting medical professionals during the analysis of risk and predisposition, disease diagnosis and prognosis, and treatment applicability and efficacy. More specific tests are also being developed to assist in ruling out, distinguishing between, and confirming suspicions of multifactorial diseases, as well as to predict which therapy option may be the best option for a given patient's biochemical profile. As more complex datasets are entering the field, involving multi-omic approaches, systems biology has stepped in to facilitate the discovery and validation steps during biomarker panel generation. Filtering biomolecules and clinical data, pre-validating and cross-validating potential biomarkers, generating final biomarker panels, and testing the robustness and applicability of those panels are all beginning to rely on machine learning and systems biology and research in this area will only benefit from advances in these approaches.

Personalization of medical treatments in oncology: time for rethinking the disease concept to improve individual outcomes

The agenda of pharmacology discovery in the field of personalized oncology was dictated by the search of molecular targets assumed to deterministically drive tumor development. In this perspective, genes play a fundamental "causal" role while cells simply act as causal proxies, i.e., an intermediate between the molecular input and the organismal output. However, the ceaseless genomic change occurring across time within the same primary and metastatic tumor has broken the hope of a personalized treatment based only upon genomic fingerprint. Indeed, current models are unable in capturing the unfathomable complexity behind the outbreak of a disease, as they discard the contribution of non-genetic factors, environment constraints, and the interplay among different tiers of organization. Herein, we posit that a comprehensive personalized model should view at the disease as a "historical" process, in which different spatially and timely distributed factors interact with each other across multiple levels of organization, which collectively interact with a dynamic gene-expression pattern. Given that a disease is a dynamic, non-linear process - and not a static-stable condition - treatments should be tailored according to the "timing-frame" of each condition. This approach can help in detecting those critical transitions through which the system can access different attractors leading ultimately to diverse outcomes - from a pre-disease state to an overt illness or, alternatively, to recovery. Identification of such tipping points can substantiate the predictive and the preventive ambition of the Predictive, Preventive and Personalized Medicine (PPPM/3PM). However, an unusual effort is required to conjugate multi-omics approaches, data collection, and network analysis reconstruction (eventually involving innovative Artificial Intelligent tools) to recognize the critical phases and the relevant targets, which could help in patient stratification and therapy personalization.

Flavonoids as an effective sensitizer for anti-cancer therapy: insights into multi-faceted mechanisms and applicability towards individualized patient profiles

Cost-efficacy of currently applied treatments is an issue in overall cancer management challenging healthcare and causing tremendous economic burden to societies around the world. Consequently, complex treatment models presenting concepts of predictive diagnostics followed by targeted prevention and treatments tailored to the personal patient profiles earn global appreciation as benefiting the patient, healthcare economy, and the society at large. In this context, application of flavonoids as a spectrum of compounds and their nano-technologically created derivatives is extensively under consideration, due to their multi-faceted anti-cancer effects applicable to the overall cost-effective cancer management, primary, secondary, and even tertiary prevention. This article analyzes most recently updated data focused on the potent capacity of flavonoids to promote anti-cancer therapeutic effects and interprets all the collected research achievements in the frame-work of predictive, preventive, and personalized (3P) medicine. Main pillars considered are: - Predictable anti-neoplastic, immune-modulating, drug-sensitizing effects; - Targeted molecular pathways to improve therapeutic outcomes by increasing sensitivity of cancer cells and reversing their resistance towards currently applied therapeutic modalities.

Machine Learning Can Predict Total Death After Radiofrequency Ablation in Liver Cancer Patients

Objective:

Over 1 million new cases of hepatocellular carcinoma (HCC) are diagnosed worldwide every year. Its prognosis remains poor, and the 5-year survival rate in all disease stages is estimated to be between 10% and 20%. Radiofrequency ablation (RFA) has become an important local treatment for liver cancer, and machine learning (ML) can provide many shortcuts for liver cancer medical research. Therefore, we explore the role of ML in predicting the total mortality of liver cancer patients undergoing RFA.

Methods:

This study is a secondary analysis of public database data from 578 liver cancer patients. We used Python for ML to establish the prognosis model.

Results:

The results showed that the 5 most important factors were platelet count (PLT), Alpha-fetoprotein (AFP), age, tumor size, and total bilirubin, respectively. Results of the total death model for liver cancer patients in test group: among the 5 algorithm models, the highest accuracy rate was that of gbm (0.681), followed by the Logistic algorithm (0.672); among the 5 algorithms, area under the curve (AUC) values, from high to low, were Logistic (0.738), DecisionTree (0.723), gbm (0.717), GradientBoosting (0.714), and Forest (0.693); Among the 5 algorithms, gbm had the highest precision rate (0.721), followed by the Logistic algorithm (0.714). Among the 5 algorithms, DecisionTree had the highest recall rate (0.642), followed by the GradientBoosting algorithm (0.571).

Conclusion:

Machine learning can predict total death after RFA in liver cancer patients. Therefore, ML research has great potential for both personalized treatment and prognosis of liver cancer.

Mitochondriopathies as a Clue to Systemic Disorders-Analytical Tools and Mitigating Measures in Context of Predictive, Preventive, and Personalized (3P) Medicine

The mitochondrial respiratory chain is the main site of reactive oxygen species (ROS) production in the cell. Although mitochondria possess a powerful antioxidant system, an excess of ROS cannot be completely neutralized and cumulative oxidative damage may lead to decreasing mitochondrial efficiency in energy production, as well as an increasing ROS excess, which is known to cause a critical imbalance in antioxidant/oxidant mechanisms and a "vicious circle" in mitochondrial injury. Due to insufficient energy production, chronic exposure to ROS overproduction consequently leads to the oxidative damage of life-important biomolecules, including nucleic acids, proteins, lipids, and amino acids, among others. Different forms of mitochondrial dysfunction (mitochondriopathies) may affect the brain, heart, peripheral nervous and endocrine systems, eyes, ears, gut, and kidney, among other organs. Consequently, mitochondriopathies have been proposed as an attractive diagnostic target to be investigated in any patient with unexplained progressive multisystem disorder. This review article highlights the pathomechanisms of mitochondriopathies, details advanced analytical tools, and suggests predictive approaches, targeted prevention and personalization of medical services as instrumental for the overall management of mitochondriopathy-related cascading pathologies.

Thirty-Day Mortality After Curative and Palliative Anti-Cancer Treatment: Data Interpretation and Lessons for Clinical Implementation

Purpose

Despite advancements in cancer therapeutics, mortality and morbidity due to anti-cancer treatments still occur but are not frequently reported. We aimed to report the 30-day mortality and morbidity of all curative and palliative anti-cancer treatments.

Patients and Methods

Adults with solid and hematological malignancies from two large cancer centers in Saudi Arabia, irrespective of the cancer stage and treatment type, were included in this retrospective observational study.

Results

Between December 1, 2019 and February 29, 2020, 1694 patients from King Abdullah Medical City in Makkah and King Fahad Medical City in Riyadh were included in the study. Among them, 77.5% were younger than 65 years of age; 72.8% were female; the prevalence of obesity, diabetes, and hypertension was 35%, 34%, and 28%, respectively; and 66.5% of patients had breast and gastrointestinal cancers. Fifty-nine (3.5%) patients died within 30 days of receiving anti-cancer treatment. Of them, 9 (0.3%) were treated with curative intent, and 50 (3%) were treated with palliative intent.

Conclusion

Our results emphasize the need to address preventable metabolic changes and implement innovative, predictive, preventive, and personalized medicine (PPPM) approaches focusing on patient profiles. Reporting the 30-day outcomes of all anti-cancer treatments will also allow the identification of factors underlying mortality and morbidity and lead to an improvement in oncological outcomes via innovative programs designed to improve clinical decision-making.

Cold Atmospheric Pressure Plasma (CAP) as a New Tool for the Management of Vulva Cancer and Vulvar Premalignant Lesions in Gynaecological Oncology

Vulvar cancer (VC) is a specific form of malignancy accounting for 5–6% of all gynaecologic malignancies. Although VC occurs most commonly in women after 60 years of age, disease incidence has risen progressively in premenopausal women in recent decades. VC demonstrates particular features requiring well-adapted therapeutic approaches to avoid potential treatment-related complications. Significant improvements in disease-free survival and overall survival rates for patients diagnosed with post-stage I disease have been achieved by implementing a combination therapy consisting of radical surgical resection, systemic chemotherapy and/or radiotherapy. Achieving local control remains challenging. However, mostly due to specific anatomical conditions, the need for comprehensive surgical reconstruction and frequent post-operative healing complications. Novel therapeutic tools better adapted to VC particularities are essential for improving individual outcomes. To this end, cold atmospheric plasma (CAP) treatment is a promising option for VC, and is particularly appropriate for the local treatment of dysplastic lesions, early intraepithelial cancer, and invasive tumours. In addition, CAP also helps reduce inflammatory complications and improve wound healing. The application of CAP may realise either directly or indirectly utilising nanoparticle technologies. CAP has demonstrated remarkable treatment benefits for several malignant conditions, and has created new medical fields, such as “plasma medicine” and “plasma oncology”. This article highlights the benefits of CAP for the treatment of VC, VC pre-stages, and postsurgical wound complications. There has not yet been a published report of CAP on vulvar cancer cells, and so this review summarises the progress made in gynaecological oncology and in other cancers, and promotes an important, understudied area for future research. The paradigm shift from reactive to predictive, preventive and personalised medical approaches in overall VC management is also considered.

Biobanks in the era of big data: objectives, challenges, perspectives, and innovations for predictive, preventive, and personalised medicine

Biobanking is entering the new era-era of big data. New technologies, techniques, and knowledge opened the potential of the whole domain of biobanking. Biobanks collect, analyse, store, and share the samples and associated data. Both samples and especially associated data are growing enormously, and new innovative approaches are required to handle samples and to utilize the potential of biobanking data. The data reached the quantity and quality of big data, and the scientists are facing the questions how to use them more efficiently, both retrospectively and prospectively with the aim to discover new preventive methods, optimize treatment, and follow up and to optimize healthcare processes. Biobanking in the era of big data contribute to the development of predictive, preventive, and personalised medicine, for every patient providing the right treatment at the right time. Biobanking in the era of big data contributes to the paradigm shift towards personalising of healthcare.

Flavonoids against the Warburg phenotype-concepts of predictive, preventive and personalised medicine to cut the Gordian knot of cancer cell metabolism

The Warburg effect is characterised by increased glucose uptake and lactate secretion in cancer cells resulting from metabolic transformation in tumour tissue. The corresponding molecular pathways switch from oxidative phosphorylation to aerobic glycolysis, due to changes in glucose degradation mechanisms known as the 'Warburg reprogramming' of cancer cells. Key glycolytic enzymes, glucose transporters and transcription factors involved in the Warburg transformation are frequently dysregulated during carcinogenesis considered as promising diagnostic and prognostic markers as well as treatment targets. Flavonoids are molecules with pleiotropic activities. The metabolism-regulating anticancer effects of flavonoids are broadly demonstrated in preclinical studies. Flavonoids modulate key pathways involved in the Warburg phenotype including but not limited to PKM2, HK2, GLUT1 and HIF-1. The corresponding molecular mechanisms and clinical relevance of 'anti-Warburg' effects of flavonoids are discussed in this review article. The most prominent examples are provided for the potential application of targeted 'anti-Warburg' measures in cancer management. Individualised profiling and patient stratification are presented as powerful tools for implementing targeted 'anti-Warburg' measures in the context of predictive, preventive and personalised medicine.

Optimal multiparametric set-up modelled for best survival outcomes in palliative treatment of liver malignancies: unsupervised machine learning and 3 PM recommendations

Over the last decade, a rapid rise in deaths due to liver disease has been observed especially amongst young people. Nowadays liver disease accounts for approximately 2 million deaths per year worldwide: 1 million due to complications of cirrhosis and 1 million due to viral hepatitis and hepatocellular carcinoma. Besides primary liver malignancies, almost all solid tumours are capable to spread metastases to the liver, in particular, gastrointestinal cancers, breast and genitourinary cancers, lung cancer, melanomas and sarcomas. A big portion of liver malignancies undergo palliative care. To this end, the paradigm of the palliative care in the liver cancer management is evolving from "just end of the life" care to careful evaluation of all aspects relevant for the survivorship. In the presented study, an evidence-based approach has been taken to target molecular pathways and subcellular components for modelling most optimal conditions with the longest survival rates for patients diagnosed with advanced liver malignancies who underwent palliative treatments. We developed an unsupervised machine learning (UML) approach to robustly identify patient subgroups based on estimated survival curves for each individual patient and each individual potential biomarker. UML using consensus hierarchical clustering of biomarker derived risk profiles resulted into 3 stable patient subgroups. There were no significant differences in age, gender, therapy, diagnosis or comorbidities across clusters. Survival times across clusters differed significantly. Furthermore, several of the biomarkers demonstrated highly significant pairwise differences between clusters after correction for multiple testing, namely, "comet assay" patterns of classes I, III, IV and expression rates of calgranulin A (S100), SOD2 and profilin-all measured ex vivo in circulating leucocytes. Considering worst, intermediate and best survival curves with regard to identified clusters and corresponding patterns of parameters measured, clear differences were found for "comet assay" and S100 expression patterns. In conclusion, multi-faceted cancer control within the palliative care of liver malignancies is crucial for improved disease outcomes including individualised patient profiling, predictive models and implementation of corresponding cost-effective risks mitigating measures detailed in the paper. The "proof-of-principle" model is presented.

Half-dose fulvestrant plus anastrozole as a first-line treatment for hormone receptor-positive metastatic breast cancer: a cost-effectiveness analysis

OBJECTIVE

The S0226 trial demonstrated that the combination of half-dose fulvestrant (FUL) and anastrozole (ANA) (F&A) caused a significant improvement in overall survival (OS) versus ANA monotherapy for first-line treatment of postmenopausal women with hormone receptor-positive metastatic breast cancer (PMW-MBC (HR+)). The objective of this study was to evaluate the cost-effectiveness of F&A in the first-line treatment for PMW-MBC (HR+) in China.

DESIGN

We constructed a Markov model over a life-time horizon. The clinical outcomes and utility data were obtained from published literature. Cost data were obtained from official Chinese websites. Sensitivity analyses were performed to test result uncertainty.

SETTING

Chinese healthcare system perspective.

POPULATION

A hypothetical cohort of adult patients presenting with PMW-MBC (HR+).

INTERVENTIONS

F&A compared with full-dose FUL and ANAmonotherapy.

MAIN OUTCOME MEASURES

The main outcome of this study was the incremental cost-effectiveness ratio (ICER) and quality-adjusted life-years (QALY).

RESULTS

ANA was estimated to have the lowest cost and minimum life-years. The ICER of F&A versus ANA was US$15 665.891/QALY with incremental cost and QALY of US$12 401.120 and 0.792, respectively, which was less than the willingness-to-pay of US$29 383/QALY. Compared with F&A, FUL yielded a higher cost and a shorter lifetime; hence, it was identified as a dominated strategy. The univariate sensitivity analysis indicated the price of FUL was the most influential factor in our study. The probability that F&A was cost-effective at a threshold of US$29 383/QALY in China was 86.5%.

CONCLUSION

F&A is a cost-effective alternative to FUL and ANA monotherapy for the first-line treatment of PMW-MBC (HR+) in China. F&A is a promising first-line treatment for PMW-MBC (HR+), and more research is needed to evaluate the economy of using F&A in other countries.

The Level of Preoperative Plasma KRAS Mutations and CEA Predict Survival of Patients Undergoing Surgery for Colorectal Cancer Liver Metastases

Colorectal cancer (CRC) belongs to the most common cancers. The liver is a predominant site of CRC dissemination. Novel biomarkers for predicting the survival of CRC patients with liver metastases (CLM) undergoing metastasectomy are needed. We examined KRAS mutated circulating cell-free tumor DNA (ctDNA) in CLM patients as a prognostic biomarker, independently or in combination with carcinoembryonic antigen (CEA). Thereby, a total of 71 CLM were retrospectively analyzed. Seven KRAS G12/G13 mutations was analyzed by a ddPCR™ KRAS G12/G13 Screening Kit on QX200 Droplet Digital PCR System (Bio-Rad Laboratories, Hercules, CA, USA) in liver metastasis tissue and preoperative and postoperative plasma samples. CEA were determined by an ACCESS CEA assay with the UniCel DxI 800 Instrument (Beckman Coulter, Brea, CA, USA). Tissue KRAS positive liver metastases was detected in 33 of 69 patients (47.8%). Preoperative plasma samples were available in 30 patients and 11 (36.7%) were KRAS positive. The agreement between plasma- and tissue-based KRAS mutation status was 75.9% (22 in 29; kappa 0.529). Patients with high compared to low levels of preoperative plasma KRAS fractional abundance (cut-off 3.33%) experienced shorter overall survival (OS 647 vs. 1392 days, p = 0.003). The combination of high preoperative KRAS fractional abundance and high CEA (cut-off 3.33% and 4.9 µg/L, resp.) best predicted shorter OS (HR 13.638, 95%CI 1.567–118.725) in multivariate analysis also (OS HR 44.877, 95%CI 1.59–1266.479; covariates: extend of liver resection, biological treatment). KRAS mutations are detectable and quantifiable in preoperative plasma cell-free DNA, incompletely overlapping with tissue biopsy. KRAS mutated ctDNA is a prognostic factor for CLM patients undergoing liver metastasectomy. The best prognostic value can be reached by a combination of ctDNA and tumor marker CEA.

Carotenoids in Cancer Apoptosis-The Road from Bench to Bedside and Back

An incidence and mortality of cancer are rapidly growing worldwide, especially due to heterogeneous character of the disease that is associated with irreversible impairment of cellular homeostasis and function. Targeting apoptosis, one of cancer hallmarks, represents a potent cancer treatment strategy. Carotenoids are phytochemicals represented by carotenes, xanthophylls, and derived compounds such as apocarotenoids that demonstrate a broad spectrum of anti-cancer effects involving pro-apoptotic signaling through extrinsic and intrinsic pathways. As demonstrated in preclinical oncology research, the apoptotic modulation is performed at post-genomic levels. Further, carotenoids demonstrate additive/synergistic action in combination with conventional oncostatic agents. In addition, a sensitization of tumor cells to anti-cancer conventional treatment can be achieved by carotenoids. The disadvantage of anti-cancer application of carotenoids is associated with their low solubility and, therefore, poor bioavailability. However, this deficiency can be improved by using nanotechnological approaches, solid dispersions, microemulsions or biofortification that significantly increase the anti-cancer and pro-apoptotic efficacy of carotenoids. Only limited number of studies dealing with apoptotic potential of carotenoids has been published in clinical sphere. Pro-apoptotic effects of carotenoids should be beneficial for individuals at high risk of cancer development. The article considers the utility of carotenoids in the framework of 3P medicine.

Liquid Biopsy is Instrumental for 3PM Dimensional Solutions in Cancer Management

One in every four deaths is due to cancer in Europe. In view of its increasing incidence, cancer became the leading cause of death and disease burden in Denmark, France, the Netherlands, and the UK. Without essential improvements in cancer prevention, an additional 775,000 cases of annual incidence have been prognosed until 2040. Between 1995 and 2018, the direct costs of cancer doubled from EUR 52 billion to EUR 103 billion in Europe, and per capita health spending on cancer increased by 86% from EUR 105 to EUR 195 in general, whereby Austria, Germany, Switzerland, Benelux, and France spend the most on cancer care compared to other European countries. In view of the consequent severe socio-economic burden on society, the paradigm change from a reactive to a predictive, preventive, and personalized medical approach in the overall cancer management is essential. Concepts of predictive, preventive, and personalized medicine (3PM) demonstrate a great potential to revise the above presented trends and to implement cost-effective healthcare that benefits the patient and society as a whole. At any stage, application of early and predictive diagnostics, targeted prevention, and personalization of medical services are basic pillars making 3PM particularly attractive for the patients as well as ethical and cost-effective healthcare. Optimal 3PM approach requires novel instruments such as well-designed liquid biopsy application. This review article highlights current achievements and details liquid biopsy approaches specifically in cancer management. 3PM-relevant expert recommendations are provided.

SCCA-IgM in hepatocellular carcinoma patients treated with transarterial chemoembolization: gender-related differences

Aim: Squamous cell carcinoma antigen immune complexed with immunoglobulin M (SCCA-IgM) is a useful but not completely satisfactory biomarker of hepatocellular carcinoma (HCC). Considering its gender-specific behavior in preclinical models, we investigated gender-related differences of SCCA-IgM as a prognostic marker in HCC. Patients & methods: Two hundred and eight prospectively recruited patients treated with transarterial chemoembolization in a single tertiary care hospital were retrospectively evaluated. Correlations between SCCA-IgM levels, clinical characteristics and survival were assessed according to gender. Results: When the disease was advanced, SCCA-IgM was higher in males and lower in females. Levels below 130 AU/ml predicted a significantly longer survival in males (p = 0.007) and a shorter survival in females (p = 0.01). Conclusion: In predicting the prognosis of HCC patients, the interpretation of SCCA-IgM should consider gender as a relevant variable.

Serum AMDL DR-70 levels: a new concept in the diagnosis and follow-up of colorectal carcinoma

Aim: The purpose of this study was to determine the diagnostic potential of DR-70 assay in patients with colorectal cancer and to investigate the relationship between serum DR-70 levels and the biological characteristic of the tumor. Patients & methods: The experimental group included patients who were diagnosed with colorectal adenocarcinoma after biopsy specimen. The control group of this study consisted of patients whose total colonoscopy was reported as normal. Results: Serum levels of DR-70 was found to be significantly higher in patients with colorectal cancer than healthy participants (p = 0.001). Receiver operating curve analyses indicated a cut-off value of 1.69 μg/ml for serum DR-70 levels. Stage of the disease, grade of the tumor, number of metastatic lymph nodes and microsatellite instability status were significantly related to serum DR-70 levels (p = 0.001, p = 0.001, p = 0.001 and p = 0.002, respectively). Conclusion: It can be concluded that serum levels of DR-70 can be regarded as an indicator for the diagnosis of colorectal cancer.

Aberrantly Methylated cfDNA in Body Fluids as a Promising Diagnostic Tool for Early Detection of Breast Cancer

Breast malignancies are the leading type of cancer among women. Its prevention and early detection, particularly in young women, remains challenging. To this end, cell-free DNA (cfDNA) detected in body fluids demonstrates great potential for early detection of tissue transformation and altered molecular setup, such as epigenetic profiles. Aberrantly methylated cfDNA in body fluids could therefore serve as a potential diagnostic and prognostic tool in breast cancer management. Abnormal methylation may lead to both an activation of oncogenes via hypomethylation and an inactivation of tumor suppressor genes by hypermethylation. We update the state of the art in the area of aberrant cfDNA methylation analyses as a diagnostic and prognostic tool in breast cancer, report on the main technological challenges, and provide an outlook for advancing the overall management of breast malignancies based on cfDNA as a target for diagnosis and tailored therapies.

Efficacy and safety of nivolumab plus apatinib in advanced liver carcinosarcoma: a case report

Liver carcinosarcoma is a rare malignancy usually seen in adults, majority of whom have a history of chronic hepatitis. Radical resection in early stages leads to better prognosis; however, the treatment regimen for patients at advanced stage is usually based on previously published case reports. At present, there is no report on programmed death-1 blockade and liver carcinosarcoma. Here, we report the case of a patient with advanced liver carcinosarcoma treated with nivolumab plus apatinib, which resulted in partial remission. However, grade 3 elevation of aminotransferase occurred during treatment, suggesting that the combination therapy should be recommended only after risk assessment. Nonetheless, programmed death-1 blockade plus apatinib might be a promising therapeutic approach for patients with advanced liver carcinosarcoma.

Label-free quantitative identification of abnormally ubiquitinated proteins as useful biomarkers for human lung squamous cell carcinomas

BACKGROUND

Ubiquitination is an important molecular event in lung squamous cell carcinoma (LSCC), which currently is mainly studied in nonsmall cell lung carcinoma cell models but lacking of ubiquitination studies on LSCC tissues. Here, we presented the ubiquitinated protein profiles of LSCC tissues to explore ubiquitination-involved molecular network alterations and identify abnormally ubiquitinated proteins as useful biomarkers for predictive, preventive, and personalized medicine (PPPM) in LSCC.

METHODS

Anti-ubiquitin antibody-based enrichment coupled with LC-MS/MS was used to identify differentially ubiquitinated proteins (DUPs) between LSCC and control tissues, followed by integrative omics analyses to identify abnormally ubiquitinated protein biomarkers for LSCC.

RESULTS

Totally, 400 DUPs with 654 ubiquitination sites were identified,, and motifs A-X (1/2/3)-K* were prone to be ubiquitinated in LSCC tissues. Those DUPs were involved in multiple molecular network systems, including the ubiquitin-proteasome system (UPS), cell metabolism, cell adhesion, and signal transduction. Totally, 44 hub molecules were revealed by protein-protein interaction network analysis, followed by survival analysis in TCGA database (494 LSCC patients and 20,530 genes) to obtain 18 prognosis-related mRNAs, of which the highly expressed mRNAs VIM and IGF1R were correlated with poorer prognosis, while the highly expressed mRNA ABCC1 was correlated with better prognosis. VIM-encoded protein vimentin and ABCC1-encoded protein MRP1 were increased in LSCC, which were all associated with poor prognosis. Proteasome-inhibited experiments demonstrated that vimentin and MRP1 were degraded through UPS. Quantitative ubiquitinomics found ubiquitination level was decreased in vimentin and increased in MRP1 in LSCC. These findings showed that the increased vimentin in LSCC might be derived from its decreased ubiquitination level and that the increased MRP1 in LSCC might be derived from its protein synthesis > degradation. GSEA and co-expression gene analyses revealed that VIM and MRP1 were involved in multiple crucial biological processes and pathways. Further, TRIM2 and NEDD4L were predicted as E3 ligases to regulate ubiquitination of vimentin and MRP1, respectively.

CONCLUSION

These findings revealed ubiquitinomic variations and molecular network alterations in LSCC, which is in combination with multiomics analysis to identify ubiquitination-related biomarkers for in-depth insight into the molecular mechanism and therapeutic targets and for prediction, diagnosis, and prognostic assessment of LSCC.

Comparing Quality of Life in Breast Cancer Patients Who Underwent Mastectomy Versus Breast-Conserving Surgery: A Meta-Analysis

: The purpose of our study was to carry out a meta-analysis of current literature to determine whether total mastectomy and breast-conserving surgery induce different outcomes in quality of life, based on the breast-cancer-specific module of the European Organizaation for Research and Treatment of Cancer core questionnaire (EORTC QLQ-BR23) used postoperatively. A systematic literature search of PubMed and EMBASE was conducted. Observational clinical studies that compared the quality of life in different surgery groups and presented empirical findings were selected. Six studies met the inclusion criteria. Breast-conserving surgery has statistically significant better outcomes than mastectomy in three of the eight outcomes measured in the EORTC QLQ-BR23, namely body image (standard mean difference, SMD = 1.742, 95% CI 0.579-2.905, p = 0.003), future perspective (SMD = 0.606, 95% CI 0.075-1.138, p = 0.025) and systemic therapy side effects (SMD = -0.641, 95% CI 0.101-1.181, p = 0.020). Our study highlighted that breast-conserving surgery was preferred over mastectomy because breast-conserving surgery leads to better outcomes in body image, future perspectives and less systemic side effects.

Quantitative Analysis of Proteome in Non-functional Pituitary Adenomas: Clinical Relevance and Potential Benefits for the Patients

Background: Non-functional pituitary adenoma (NFPA) is a common tumor that occurs in the pituitary gland, and generally without any symptoms at its early stage and without clinical elevation of hormones, which is commonly diagnosed when it grows up to compress its surrounding tissues and organs. Currently, the pathogenesis of NFPA has not been clarified yet. It is necessary to investigate molecular alterations in NFPA, and identify reliable biomarkers and drug therapeutic targets for effective treatments. Methods: Tandem mass tags (TMT)-based quantitative proteomics was used to identify and quantify proteins in NFPAs. GO and KEGG enrichment analyses were used to analyze the identified proteins. Differentially expressed genes (DEGs) between NFPA and control tissues were obtained from GEO datasets. These two sets of protein and gene data were analyzed to obtain overlapped molecules (genes; proteins), followed by further GO and KEGG pathway analyses of these overlapped molecules, and molecular network analysis to obtain the hub molecules with Cytoscape. Two hub molecules (SRC and AKT1) were verified with Western blotting. Results: Totally 6076 proteins in NFPA tissues were identified, and 3598 DEGs between NFPA and control tissues were identified from GEO database. Overlapping analysis of 6076 proteins and 3598 DEGs obtained 1088 overlapped molecules (DEGs; proteins). KEGG pathway analysis of 6076 proteins obtained 114 statistically significant pathways, including endocytosis, and spliceosome signaling pathways. KEGG pathway analysis of 1088 overlapped molecules obtained 52 statistically significant pathways, including focal adhesion, cGMP-PKG pathway, and platelet activation signaling pathways. These pathways play important roles in cell energy supply, adhesion, and maintenance of the tumor microenvironment. According to the association degree in Cytoscape, ten hub molecules (DEGs; proteins) were identified, including GAPDH, ALB, ACACA, SRC, ENO2, CALM1, POTEE, HSPA8, DECR1, and AKT1. Western-blotting analysis confirmed the upregulated expressions of SRC and PTMScan experiment confirmed the increased levels of pAKT1, in NFPAs compared to controls. Conclusions: This study established the large-scale quantitative protein profiling of NFPA tissue proteome. It offers a basis for subsequent in-depth proteomics analysis of NFPAs, and insight into the molecular mechanism of NFPAs. It also provided the basic data to discover reliable biomarkers and therapeutic targets for NFPA patients.

TMT-based quantitative proteomics revealed follicle-stimulating hormone (FSH)-related molecular characterizations for potentially prognostic assessment and personalized treatment of FSH-positive non-functional pituitary adenomas

BACKGROUND

Non-functional pituitary adenoma (NFPA) is highly heterogeneous with different hormone expression subtypes. Of them, follicle-stimulating hormone (FSH)-positive expression is an important subtype of NFPAs. It is well-known that FSH exerted its functions through binding its receptor. However, the expression rate of FSH receptor was significantly higher in aggressive pituitary adenomas. This study aimed to investigate the molecular characteristics of FSH-positive NFPAs for effective stratification of patient, target treatment, prognostic assessment, and personalized treatment of FSH-positive NFPAs.

METHODS

Tandem mass tag (TMT)-based quantitative proteomics was used to investigate differentially expressed proteins (DEPs) between FSH-positive and negative NFPAs. Gene ontology and KEGG pathway enrichment analyses were used to analyze the DEPs. Differentially expressed genes (DEGs) between invasive and non-invasive NFPAs from GEO database were analyzed with pathway enrichment analysis. Protein-protein interaction (PPI) networks were constructed based on DEPs in excetral cellular matrix (ECM)-receptor interaction, focal adhesion, and PI3K-Akt pathways. Cytoscape was used to obtain most significant modules. Western blot was used to validate the expressions of upregulated proteins (ITGA1, ITGA6, and ITGB4), the expression and phosphorylated status of Akt in PI3K-Akt pathway, and the expression of FSH receptors in FSH-positive relative to negative NFPAs.

RESULTS

A total of 594 DEPs (374 upregulated and 220 downregulated) were identified between FSH-positive and negative NFPAs. Nineteen KEGG pathway networks were identified to involve DEPs, and reveal molecular differences between FSH-positive and negative NFPAs, including three important pathways that were significantly associated with tumor invasiveness and aggressiveness: ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathways. Further, focal adhesion pathway was also confirmed with invasiveness-related NFPA DEG data that were derived from GEO database. Moreover, the significantly upregulated DEPs (ITGA1, ITGA6, and ITGB4) that were associated with tumor invasiveness and aggressiveness were confirmed by immunoaffinity analysis in FSH-positive vs. negative NFPAs. Also, the phosphorylation level but not its expression level of AKT in PI3K-AKT signaling was significantly increased, and the expression level of FSH receptor was significantly increased in FSH-positive relative to negative NFPAs. Also, overlapping analysis of 594 DEPs and 898 DEGs revealed 45 invasiveness-related DEPs, including 11 upregulated DEPs (ITGA6, FARP1, PALLD, PPBP, LIMA1, SCD, UACA, BAG3, CLU, PLEC, and GATM) that were also upregulated genes in invasive NFPAs, and 8 downregulated DEPs (ALCAM, HP, FSTL4, IL13RA2, NPTX2, DPP6, CRABP2, and SLC27A2) that were also downregulated genes in invasive NFPAs.

CONCLUSIONS

FSH-positive expression was an important NFPA subtype. It was the first time for this study to reveal FSH-related proteomic variations and the corresponding molecular network alterations in FSH-positive relative to negative NFPAs. Also, three signaling pathways (ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathways) and involved upregulated proteins (ITGA1, ITGA6, ITGB4, pAKT, and FSHR) were significantly associated with tumor invasiveness and aggressiveness, and a set of invasiveness-related DEPs were identified with overlapping analysis of 594 DEPs in FSH-positive vs. negative NFPAs and 898 DEGs in invasive vs. non-invasive NFPAs. These findings offered the scientific evidence to in-depth understand molecular characteristics of FSH-positive NFPAs, and effectively stratify the post-surgery patients for personalized prognostic assessment and targeted treatment of FSH-positive NFPAs.

Platelet Volume Is Reduced In Metastasing Breast Cancer: Blood Profiles Reveal Significant Shifts

Background

Platelets play a crucial role in breast cancer (BC) progression and metastases. Mean platelet volume (MPV) is an indicator of platelet activation. The aim of the present study was to assess whether there is a difference in MPV between patients with metastatic BC with liver metastases and those with BC without liver metastases.

Methods

Between January 2014 and December 2017, 211 metastatic BC patients with synchronous liver metastases and 215 BC patients without metastases were retrospectively analyzed. Patients’ clinicopathological characteristics data were collected.

Results

MPV levels were reduced in patients with liver metastases compared with those in patients without liver metastases. There were significant differences in MPV levels according to liver metastases status both in premenopausal and in postmenopausal non-TNBC or non-HER2+ patients. Moreover, in postmenopausal HER2+ or TNBC patients, MPV levels were lower in patients with liver metastases compared with those in patients without liver metastases. In the group with non-liver metastasis, platelet distribution width was significantly associated with tumor N stage. In addition, the prevalence of BC liver metastases decreased as MPV quartiles increased. After adjusting for other risk factors, the odds ratios for liver metastases according to MPV quartiles were 1.000, 0.267 (0.134–0.530), 0.072 (0.034–0.152), and 0.137 (0.066–0.281), respectively.

Conclusion

MPV is reduced in BC patients with liver metastases compared with that in BC patients without metastases. Moreover, MPV is independently associated with the presence of liver metastases.

Reduced chemotherapeutic sensitivity in high glucose condition: implication of antioxidant response

Resistance to chemotherapy represents a major obstacle to successful treatment. The generation of reactive oxygen species (ROS) has been directly linked to the cytotoxic effects of several antitumor agents, including Adriamycin (ADR), and modulation of the oxidative balance has been implicated in the development and/or regulation of resistance to chemotherapeutic drugs. We recently showed that high glucose (HG) markedly diminished the cancer cell death induced by anticancer agents such as ADR. In the present study we attempted to evaluate the mechanism that impaired the cytotoxic effect of ADR in HG. We found that, in colon cancer cells, HG attenuated ADR-induced ROS production that consequently diminished ADR-induced H2AX phosphorylation and micronuclei (MN) formation. Mechanistically, HG attenuation of ADR-induced ROS production correlated with increased antioxidant response promoted by NRF2 activity. Thus, pharmacologic inhibition of NRF2 pathway by brusatol re-established the ADR cytotoxic effect impaired by HG. Together, the data provide new insights into chemotherapeutic-resistance mechanisms in HG condition dictated by increased NRF2-induced antioxidant response and how they may be overcome in order to restore chemosensitivity and ADR-induced cell death.

Why the Gold Standard Approach by Mammography Demands Extension by Multiomics? Application of Liquid Biopsy miRNA Profiles to Breast Cancer Disease Management

In the global context, the epidemic of breast cancer (BC) is evident for the early 21st century. Evidence shows that national mammography screening programs have sufficiently reduced BC related mortality. Therefore, the great utility of the mammography-based screening is not an issue. However, both false positive and false negative BC diagnosis, excessive biopsies, and irradiation linked to mammography application, as well as sub-optimal mammography-based screening, such as in the case of high-dense breast tissue in young females, altogether increase awareness among the experts regarding the limitations of mammography-based screening. Severe concerns regarding the mammography as the “golden standard” approach demanding complementary tools to cover the evident deficits led the authors to present innovative strategies, which would sufficiently improve the quality of the BC management and services to the patient. Contextually, this article provides insights into mammography deficits and current clinical data demonstrating the great potential of non-invasive diagnostic tools utilizing circulating miRNA profiles as an adjunct to conventional mammography for the population screening and personalization of BC management.

Blood biomarker panel recommended for personalized prediction, prognosis, and prevention of complications associated with abdominal aortic aneurysm

The aim of the study was to evaluate the ability of following biomarkers as diagnostic tools and risk predictors of AAA: C-reactive protein, interleukin-6, pentraxin-3, galectin-3, procollagen type III N-terminal peptide, C-terminal telopeptide of type I collagen, high-sensitive troponin I, and brain natriuretic peptide. Seventy-two patients with an AAA and 100 healthy individuals were enrolled into the study. We assessed individual biomarker performance and correlation between the AAA diameter and biomarker levels, and also, a multivariate logistic regression was used to design a possible predictive model of AAA growth and rupture risk. We identified following four parameters with the highest potential to find a useful place in AAA diagnostics: galectin-3, pentraxin-3, interleukin-6, and C-terminal telopeptide of type I. The best biomarkers in our evaluation (galectin-3 and pentraxin-3) were AAA diameter-independent. With the high AUC and AAA diameter correlation, the high-sensitive troponin I can be used as an independent prognostic biomarker of the upcoming heart complications in AAA patients. Authors recommend to add biomarkers as additional parameters to the current AAA patient management. Main addition value of biomarkers is in the assessment of the AAA with the smaller diameter. Elevated biomarkers can change the treatment decision, which would be done only based on AAA diameter size. The best way how to manage the AAA patients is to create a reliable predictive model of AAA growth and rupture risk. A created multiparameter model gives very promising results with the significantly higher efficiency compared with the use of the individual biomarkers.

Knockdown of Golgi phosphoprotein 73 blocks the trafficking of matrix metalloproteinase-2 in hepatocellular carcinoma cells and inhibits cell invasion

Golgi phosphoprotein 73 (GP73) has been regarded as a novel serum biomarker for the diagnosis of hepatocellular carcinoma (HCC) in recent years. It has been reported that the upregulation of GP73 may promote the carcinogenesis and metastasis of HCC; however, the mechanisms remain poorly understood. In this study, GP73 correlates positively with matrix metalloproteinase‐2 (MMP‐2) in HCC‐related cells and tissues. Further studies indicate that the knockdown of GP73 blocks MMP‐2 trafficking and secretion, resulting in cell invasion inhibition. Additionally, the knockdown of GP73 induces the accumulation of intracellular MMP‐2, which inhibits the phosphorylation of Src at Y416 and triggers the inhibition of SAPK/JNK and p53‐p21 signalling pathways through a negative feedback loop. Finally, the transactivation of MMP2 was inhibited by the reduction in E2F1. This study reveals that GP73 plays functional roles in the trafficking and equilibrium of epithelial‐mesenchymal transition (EMT)‐related secretory proteins and that GP73 serves as a new potential target for combating the metastasis of HCC.