Multiple biomarkers in molecular oncology. II. Molecular diagnostics applications in breast cancer management

A Study on the Application of Extended Care Based on the Biopsychosocial Medicine Model in People with Abnormal Tumor Markers on Physical Examination

The purpose of this study was to explore the value of extended care based on a biopsychosocial medicine model in patients with abnormal tumor markers on physical examination. One hundred and fifty-two cases with abnormal primary screening tumor markers who were examined in our medical examination center between January 2020 and January 2022 were selected as the subjects of this study and divided into intervention and control groups according to the random number table method, with 76 cases in each group. The control group was given the usual extended care intervention and the intervention group was given the extended care intervention based on the biopsychosocial medicine model. The compliance rates of regular follow-up, reasonable diet, appropriate exercise, and regular rest were compared between the two groups. After the intervention, the disease-related knowledge score in the intervention group was higher than that in the control group ( $P<0.05$ ). The compliance rates of regular return visits, reasonable diet, appropriate exercise, and regular routines in the intervention group were higher than those in the control group ( $P<0.05$ ). After the intervention, the scores of psychological states such as anxiety, depression, and post-traumatic growth in the intervention group were better than those in the control group ( $P<0.05$ ). After the intervention, the total scores of objective support, subjective support, support utilization, and social support in the intervention group were higher than those in the control group ( $P<0.05$ ). After the intervention, the intervention group had higher positive coping scores and lower negative coping scores than the control group ( $P<0.05$ ). Continuing care based on the biopsychosocial model of medicine is effective in people with abnormal tumor markers on medical screening. It can improve the knowledge about the disease, increase the compliance rate, improve negative emotions, psychological status, and social support, and promote a more positive way of responding.

Correlation of expression of Akt1 and E2F1 and their phosphorylated forms in breast cancer patients with clinicopathological parameters

Breast cancer is the leading cancer worldwide among women. Traditional clinicopathological prognostic and predictive markers need refining to improve clinical outcomes. This study explored the association between traditional clinicopathological factors and the expression of Akt1 and E2F1 transduction proteins and their phosphorylated forms in breast cancer, to determine their value as novel biomarkers and potential therapeutic targets. Tumor tissues from 94 female breast cancer patients were examined for immunophenotypic expression of total Akt1, pAkt1 (Serine 473), pAkt1 (Threonine 308), total E2F1, pE2F1 (Thr433) and pE2F1 (Ser337). The expression of pAkt1 (Ser473) was significantly associated with ER/PR positive status and total E2F1 with older age (> 50), lymph node involvement and HER2 positivity. There was a significant association between triple negative cancers and total and pAkt1 (Thr308). pAkt1 (Ser473) showed an inverse relationship with Luminal B cancers and pE2F1 (Thr433) showed an inverse association with triple negative cancers. Higher expression of pE2F1 (Ser337) was associated with better OS. Both pAkt1 (Ser473 and Thr308) proteins showed significant association with poorer patient outcomes. E2F1 (Ser337) showed a significant positive correlation with response to chemotherapy. The study suggests that a pAkt1^-/pE2F1⁺ phenotype could indicate an opportunity to minimize chemotherapeutic options in older women; conversely a pAkt1⁺/pE2F1^- phenotype could prompt a more aggressive regimen. Further exploration of this phenotype in younger women with breast cancer and triple-negative breast cancers is warranted.

Vinorelbine with or without Trastuzumab in Metastatic Breast Cancer: A Retrospective Single Institution Series

Background. We report our experience with vinorelbine, a widely used chemotherapeutic, in unselected metastatic breast cancer patients treated in clinical routine. Patients and Methods. The data of all patients with metastatic breast cancer receiving vinorelbine with or without trastuzumab during a six year period were reviewed. Patients received vinorelbine intravenous 25–30 mg/m² or 60–80 mg/m² orally in days 1 and 8 of a 21 day cycle. Results. Eighty-seven women were included. Sixty-two patients received vinorelbine alone and 25 patients received vinorelbine in combination with trastuzumab. In 67 patients this was the first line treatment for metastatic disease and in 20 patients it was 2nd or later line of treatment. The median TTP was six months (range: 1–45). The median overall survival was 11.5 months (range: 1–83). Seventy patients were evaluable for response. In patients receiving first line treatment 44.4% had a response while in the second and subsequent lines setting 12.5% of patients responded (P = 0.001). Objective response was obtained in 63.6% of patients receiving concomitant trastuzumab and in 25% of patients receiving vinorelbine alone (P = 0.0002). Conclusion. This study confirms a high disease control rate. Response rate and TTP were superior in first line treatment compared to subsequent lines.

Functional biomarkers of depression: diagnosis, treatment, and pathophysiology

Major depressive disorder (MDD) is a heterogeneous illness for which there are currently no effective methods to objectively assess severity, endophenotypes, or response to treatment. Increasing evidence suggests that circulating levels of peripheral/serum growth factors and cytokines are altered in patients with MDD, and that antidepressant treatments reverse or normalize these effects. Furthermore, there is a large body of literature demonstrating that MDD is associated with changes in endocrine and metabolic factors. Here we provide a brief overview of the evidence that peripheral growth factors, pro-inflammatory cytokines, endocrine factors, and metabolic markers contribute to the pathophysiology of MDD and antidepressant response. Recent preclinical studies demonstrating that peripheral growth factors and cytokines influence brain function and behavior are also discussed along with their implications for diagnosing and treating patients with MDD. Together, these studies highlight the need to develop a biomarker panel for depression that aims to profile diverse peripheral factors that together provide a biological signature of MDD subtypes as well as treatment response.

Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies

Background

In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant differentially expressed genes. Later, researchers moved toward the systematic integration of gene expression profiles with additional biological information, such as chromosomal location, ontological annotations or sequence features. The analysis of gene expression linked to physical location of genes on chromosomes allows the identification of transcriptionally imbalanced regions, while, Gene Set Analysis focuses on the detection of coordinated changes in transcriptional levels among sets of biologically related genes.

In this field, meta-analysis offers the possibility to compare different studies, addressing the same biological question to fully exploit public gene expression datasets.

Results

We describe STEPath, a method that starts from gene expression profiles and integrates the analysis of imbalanced region as an a priori step before performing gene set analysis. The application of STEPath in individual studies produced gene set scores weighted by chromosomal activation. As a final step, we propose a way to compare these scores across different studies (meta-analysis) on related biological issues. One complication with meta-analysis is batch effects, which occur because molecular measurements are affected by laboratory conditions, reagent lots and personnel differences. Major problems occur when batch effects are correlated with an outcome of interest and lead to incorrect conclusions. We evaluated the power of combining chromosome mapping and gene set enrichment analysis, performing the analysis on a dataset of leukaemia (example of individual study) and on a dataset of skeletal muscle diseases (meta-analysis approach).

In leukaemia, we identified the Hox gene set, a gene set closely related to the pathology that other algorithms of gene set analysis do not identify, while the meta-analysis approach on muscular disease discriminates between related pathologies and correlates similar ones from different studies.

Conclusions

STEPath is a new method that integrates gene expression profiles, genomic co-expressed regions and the information about the biological function of genes. The usage of the STEPath-computed gene set scores overcomes batch effects in the meta-analysis approaches allowing the direct comparison of different pathologies and different studies on a gene set activation level.

DNA diagnostics: nanotechnology-enhanced electrochemical detection of nucleic acids

The detection of mismatched base pairs in DNA plays a crucial role in the diagnosis of genetic-related diseases and conditions, especially for early stage treatment. Among the various biosensors that have been used for DNA detection, EC sensors show great promise because they are capable of precise DNA recognition and efficient signal transduction. Advancements in micro- and nanotechnologies, specifically fabrication techniques and new nanomaterials, have enabled for the development of highly sensitive, highly specific sensors making them attractive for the detection of small sequence variations. Furthermore, the integration of sensors with sample preparation and fluidic processes enables for rapid, multiplexed DNA detection essential for POC clinical diagnostics.

Molecular markers of breast axillary lymph node metastasis

In breast cancer, axillary lymph node status is one of the most important prognostic variables and a crucial component to the staging system. Several clinico-histopathological parameters are considered to be strong predictors of metastasis; however, they fail to accurately classify breast tumors according to their clinical behavior and to predict which patients will have disease recurrence. Methods based on genome-wide microarray analyses have been used to identify molecular markers with respect to the development of axillary lymph node metastasis. Most of these markers can be detected in the primary tumors, which can potentially lead to the ability to identify patients at the time of diagnosis who are at high risk for lymph node metastasis, allowing for early intervention and more suitable adjuvant treatments.

Postal survey of physicians and laboratories: practices and perceptions of molecular oncology testing

Background

Molecular oncology testing (MOT) to detect genomic alterations underlying cancer holds promise for improved cancer care. Yet knowledge limitations regarding the delivery of testing services may constrain the translation of scientific advancements into effective health care.

Methods

We conducted a cross-sectional, self-administered, postal survey of active cancer physicians in Ontario, Canada (N = 611) likely to order MOT, and cancer laboratories (N = 99) likely to refer (i.e., referring laboratories) or conduct (i.e., testing laboratories) MOT in 2006, to assess respondents' perceptions of the importance and accessibility of MOT and their preparedness to provide it.

Results

54% of physicians, 63% of testing laboratories and 60% of referring laboratories responded. Most perceived MOT to be important for treatment, diagnosis or prognosis now, and in 5 years (61% – 100%). Yet only 45% of physicians, 59% of testing labs and 53% of referring labs agreed that patients in their region were receiving MOT that is indicated as a standard of care. Physicians and laboratories perceived various barriers to providing MOT, including, among 70% of physicians, a lack of clear guidelines regarding clinical indications, and among laboratories, a lack of funding (73% – 100%). Testing laboratories were confident of their ability to determine whether and which MOT was indicated (77% and 82% respectively), and perceived that key elements of formal and continuing education were helpful (75% – 100%). By contrast, minorities of physicians were confident of their ability to assess whether and which MOT was indicated (46% and 34% respectively), and while majorities considered various continuing educational resources helpful (68% – 75%), only minorities considered key elements of formal education helpful in preparing for MOT (17% – 43%).

Conclusion

Physicians and laboratory professionals were enthusiastic about the value of MOT for cancer care but most did not believe patients were gaining adequate access to clinically necessary testing. Further, our results suggest that many were ill equipped as individual stakeholders, or as a coordinated system of referral and interpretation, to provide MOT. These challenges should inspire educational, training and other interventions to ensure that developments in molecular oncology can result in optimal cancer care.

Defining human diabetic nephropathy on the molecular level: integration of transcriptomic profiles with biological knowledge

Diabetic nephropathy (DN) is the most common cause for end stage renal disease (ESRD). Next to environmental factors, genetic predispositions determine the susceptibility for DN and its rate of progression to ESRD. With the availability of genome wide expression profiling we have the opportunity to define relevant pathways activated in the individual diabetic patient, integrating both environmental exposure and genetic background. In this review we summarize current understanding of how to link comprehensive gene expression data sets with biomedical knowledge and present strategies to build a transcriptional network of DN. Information about the individual disease processes of DN might allow the implementation of a personalized molecular medicine approach with mechanism-based patient management. Web based search engines like Nephromine are essential tools to facilitate access to molecular data of genomics, proteomics and metabolomics of DN.

Development and verification of a prediction model using serum tumor markers to predict the response to chemotherapy of patients with metastatic or recurrent breast cancer

PURPOSE

The aim of this study was to develop a prediction model using serum tumor markers to predict the response to chemotherapy of patients with metastatic or recurrent breast cancer.

METHODS

We retrospectively analyzed a training set of 105 patients with metastatic or recurrent breast cancer. Their chemotherapeutic response had been evaluated according to the World Health Organization (WHO)'s response criteria. Our model for predicting response using carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 15-3, and NCC-ST-439 was determined using the area under the receiver operating characteristic curve (ROC-AUC) and the overall misclassification rate (OMR) in a random cross-validation. The prediction model was then verified in a consecutive set of 64 patients. Their response had been evaluated using the response evaluation criteria in solid tumors (RECIST) criteria.

RESULTS

The best prediction model consisted of the serum CEA, CA15-3, and NCC-ST-439 levels, but the prediction formula varied according to the baseline CA15-3 level (elevated or normal). The overall ROC-AUC and OMR in the training set were 0.83 and 0.19, respectively. The overall ROC-AUC and OMR in the verification set were 0.72 and 0.28, respectively. When the verification set was stratified according to either the objective response or the predicted response, the time-to-progression, but not the overall survival, was significantly different.

CONCLUSION

Our model for predicting the response to first-line chemotherapy of patients with metastatic or recurrent breast cancer may be valid because it predicted the outcome of more than 70% of the patients in an independent verification set.