Immunohistochemical Predictors of Bone Metastases in Breast Cancer Patients

Understanding the Genetic Basis of Celiac Disease: A Comprehensive Review

Celiac disease is an immune-mediated enteropathy with typical symptoms of weight loss, abdominal bloating, diarrhea, vomiting, or constipation. Many shreds of evidence show that CeD is hereditary in origin and various biochemical pathways have been connected to its etiology. Numerous genes from different physiological pathways have been investigated in the last few decades, however a comprehensive analysis is required to address the gaps and provide a more integrated understanding of how these genetic factors contribute to the pathogenesis of disease. Present study attempts to summarize the historical and up-to-date findings to understand the role of genetics in Celiac disease. The literature was searched from sources such as PubMed and Google Scholar to analyze studies conducted on celiac disease from the years 1995 to 2024. Term maps were created to examine the frequency of studies related to various terms to understand the major focus of the studies till date. The study also concise the different genetic polymorphisms studied in a table to understand the role of genetics in celiac diseases. Early studies on celiac disease primarily focused on its pathophysiology, prevalence, and general aspects, with limited attention to genetics. However, recent studies have increasingly emphasized the genetic basis of the disease and highlighting the involvement of various pathways like inflammation, T-cell differentiation and activation, epithelial barrier function, stress and apoptosis pathways. However, present study indicate that most current research predominantly focus on cytokines, specifically the TNF alpha gene. Consequently, there is a need for additional research to gain a more comprehensive understanding of the genetics of celiac disease.

Correlation between ER, PR, HER-2, and Ki-67 with the risk of bone metastases detected by bone scintigraphy in breast cancer patients: A cross sectional study

BACKGROUND

Breast cancer is one of the most common cancers in women. About 30%-85% of breast cancers will metastasize to the bone during the course of the illness. Many studies have shown that molecular marker/subtypes can be useful in determining incidence of different and inconsistent bone metastases. This study aimed to determine the correlation of the risk of bone metastases in breast cancer based on the expression of molecular markers.

METHODS

The research was conducted retrospectively by searching patients' medical record data. The target population of this study was all patients diagnosed with breast cancer who came to our tertiary hospital in the Nuclear Medicine and Molecular Imaging Department from January 2012 to December 2016.

RESULTS

One hundred and thirty patients (n = 130) were enrolled during the study period with characteristics of sex, age, and immunohistochemical/molecular subtype examination that underwent bone scintigraphy. Mean of age was 50.2 (23-79) years. There were no significant correlations between ER, PR, and HER-2 expressions with bone metastases in breast cancer patients. Ki-67 was showed to be correlated with bone metastases in breast cancer patients in our bivariate analysis. Molecular subtype/markers had no statistically significant correlation with bone metastases in patients with breast cancer.

CONCLUSION

Ki-67 with high proliferation index was the most powerful molecular marker to determine the risk of bone metastases. The prevalence of bone metastases in the group with Ki-67 expression with high proliferation (≥20) was 1.8 times greater than the prevalence of bone metastases in the weakest HER-2 group.

A targeted mass spectrometry immunoassay to quantify osteopontin in fresh-frozen breast tumors and adjacent normal breast tissues

Osteopontin (OPN) is a multifunctional protein that can activate cell-signaling pathways and lead to cancer development and metastasis. Elevated OPN expression was reported in different cancer types, including breast tumors. Here, we present a new immuno-mass spectrometry method for OPN quantification in fresh-frozen malignant and adjacent normal human breast tissues. For quantification we used two proteotypic peptides: OPN-peptide-1 and OPN-peptide-2. Peptide concentrations were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode with stable isotope standards (SIS) and immuno-affinity enrichment for isolation of OPN peptides. Based on the OPN-peptide-1, the average OPN concentration in normal breast tissue was 19.42 μg/g, while the corresponding level in breast tumors was 603.9 μg/g. Based on OPN-peptide-2, the average concentration in normal breast tissue was 19.30 μg/g and in breast tumors 535.0 μg/g. In ER/PR/HER2(-) patients the OPN levels in breast tumors were significantly higher than in corresponding normal breast tissue samples, whereas in the single ER/PR/HER2(+) patient the OPN concentration in tumor samples was lower than in normal breast tissue sample. In conclusion, the current method is considered promising for the quantification of OPN in research and in clinical settings and should be further studied in breast cancer patients. SIGNIFICANCE: A new immuno-mass spectrometry method was successfully developed and applied to determine OPN concentrations in malignant tumor and normal breast tissues from six patients, and the method is promising for OPN quantification in both research and clinical settings.

Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers

BACKGROUND

Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most common underlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis. Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiple variables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed at identifying a biomarker signature to predict particular sites of DM in TNBC.

METHODS

A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, to develop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasis to each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Cox univariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariable analyses.

RESULTS

Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher risk of developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predicting site-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status.

CONCLUSIONS

Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specific sites of metastasis, and potentially unravel biomarkers previously unknown in site tropism.

Bone metastasis risk factors in breast cancer

Bone is the single most frequent site for bone metastasis in breast cancer patients. Patients with bone-only metastasis have a fairly good prognosis when compared with patients with visceral disease. Nevertheless, cancer-induced bone disease carries an important risk of developing skeletal related events that impact quality of life (QoL). It is therefore particularly important to stratify patients according to their risk of developing bone metastasis. In this context, several risk factors have been studied, including demographic, clinicopathological, genetic, and metabolic factors. Most of them show conflicting or non-definitive associations and are not validated for clinical use. Nonetheless, tumour intrinsic subtype is widely accepted as a major risk factor for bone metastasis development and luminal breast cancer carries an increased risk for bone disease. Other factors such as gene signatures, expression of specific cytokines (such as bone sialoprotein and bone morphogenetic protein 7) or components of the extracellular matrix (like bone crosslinked C-telopeptide) might also influence the development of bone metastasis. Knowledge of risk factors related with bone disease is of paramount importance as it might be a prediction tool for triggering the use of targeted agents and allow for better patient selection for future clinical trials.