Invasive Ductal Carcinoma Research Articles

A histomorphological and immunohistochemical analysis of invasive lobular carcinoma of breast: A case series

Invasive lobular carcinoma (ILC) is the second most common special subtype of invasive breast carcinoma comprising 5–15%. ILC defines as invasive carcinoma comprising non-cohesive single-file linear pattern in fibrous stroma. The aim of the study was to evaluate the histomorphological features and immunohistochemical analysis of ILC. A total of 19 cases were encountered from March 2020 to February 2024 out of 129 breast cancers. The sociodemographic profiles and clinicopathological parameters of the patients were studied with special emphasis on their morphology and hormone receptor status. The mean age of patients is 42.8 years. Out of 19 cases, 84.2% showed feature of classic type, 5.2% of tubule-lobular, and 10.5% of pleomorphic lobular carcinoma. The majority of cases (63.2%) showed histologic Grade 2, and 10.5% showed Grade 3. On immunohistochemistry examination, 79% were estrogen receptor (ER) and progesterone receptor (PR) positive with 10.5% of cases was human epidermal growth factor receptor 2/neu (HER2/neu) positive. Our study showed higher cases of classic type ILC, mostly of histologic Grade 2; higher ER-PR receptor positivity and HER2/neu negativity.

Granulomatous response within draining axillary lymph nodes in patients with Breast cancer: A series of 4 cases

Granulomatous response associated with breast cancer and within the draining lymph nodes is an extremely rare phenomenon. In this study, we are presenting a series of 4 cases of invasive ductal carcinoma showing both caseating and noncaseating granulomas within the ipsilateral draining axillary lymph nodes. We also discussed the pathogenesis of granulomatous response and its clinicopathologic significance.

Advancing Ki67 hotspot detection in breast cancer: acomparative analysis of automated digital image analysis algorithms.

Manual detection and scoring of Ki67 hotspots is difficult and prone to variability, limiting its clinical utility. Automated hotspot detection and scoring by digital image analysis (DIA) could improve the assessment of the Ki67 hotspot proliferation index (PI). This study compared the clinical performance of Ki67 hotspot detection and scoring DIA algorithms based on virtual dual staining (VDS) and deep learning (DL) with manual Ki67 hotspot PI assessment. Tissue sections of 135 consecutive invasive breast carcinomas were immunohistochemically stained for Ki67. Two DIA algorithms, based on VDS and DL, automatically determined the Ki67 hotspot PI. For manual assessment; two independent observers detected hotspots and calculated scores using a validated scoring protocol. Automated hotspot detection and assessment by VDS and DL could be performed in 73% and 100% of the cases, respectively. Automated hotspot detection by VDS and DL led to higher Ki67 hotspot PIs (mean 39.6% and 38.3%, respectively) compared to manual consensus Ki67 PIs (mean 28.8%). Comparing manual consensus Ki67 PIs with VDS Ki67 PIs revealed substantial correlation (r = 0.90), while manual consensus versus DL Ki67 PIs demonstrated high correlation (r = 0.95). Automated Ki67 hotspot detection and analysis correlated strongly with manual Ki67 assessment and provided higher PIs compared to manual assessment. The DL-based algorithm outperformed the VDS-based algorithm in clinical applicability, because it did not depend on virtual alignment of slides and correlated stronger with manual scores. Use of a DL-based algorithm may allow clearer Ki67 PI cutoff values, thereby improving the clinical usability of Ki67.

Magnetic resonance imaging insights from active surveillance of women with ductal carcinoma in situ

New approaches are needed to determine which ductal carcinoma in situ (DCIS) is at high risk for progression to invasive ductal carcinoma (IDC). We retrospectively studied DCIS patients who declined surgery (2002–2019), and received endocrine therapy (ET) and breast MRI. Baseline MRI and changes at 3 months and 6 months were analyzed by recursive partitioning to stratify IDC risk. Sixty-two patients (63 DCIS; 1 bilateral) with a mean follow-up of 8.5 years were included. Fifty-one percent remained on active surveillance (AS) without evidence of IDC, with a mean duration of 7.6 years. A decision tree based on MRI features of lesion distinctness and background parenchymal enhancement (BPE) at baseline and change after 3 months of ET stratified patients into low, intermediate, and high risk for progression to IDC. MRI imaging features in patients treated with ET and undergoing AS, may help determine which DCIS lesions are at low versus high risk for IDC.

IMAML-IDCG: Optimization-based meta-learning with ImageNet feature reusing for few-shot invasive ductal carcinoma grading

Model-Agnostic Meta-Learning (MAML) is a widely used few-shot learning (FSL) technique that reduces reliance on large, labeled datasets in deep learning for medical imaging analysis. However, MAML requires backpropagating through all feature layers for task adaptation, leading to suboptimal computational efficiency. We propose IMAML-IDCG (ImageNet Model-Agnostic Meta-Learning in Invasive Ductal Carcinoma Grading), which enhances computational efficiency for few-shot grading of Invasive Ductal Carcinoma (IDC) through three key techniques: (1) ImageNet feature reusing, (2) ImageNet partial freezing strategy, and (3) adaptive inner learning rate. IMAML-IDCG is initialized with ImageNet pre-trained weights. During the inner optimization loop, only the model’s classifier head layer is optimized, leveraging prior ImageNet knowledge (ImageNet feature reusing) and employing an adaptive learning rate for improved task adaptation. In the outer optimization loop, IMAML-IDCG selectively fine-tunes the last few model layers to enhance efficiency and reduce overfitting (ImageNet partial freezing strategy). We evaluated IMAML-IDCG using the BreaKHis dataset (7,909 images) as the base dataset, and the BCHI (282 images) and PathoIDCG (3,744 images) datasets as the novel datasets. Our empirical results demonstrate that IMAML-IDCG outperforms MAML and other FSL methods in few-shot IDC grading tasks across various cross-magnification domain settings. Notably, IMAML-IDCG achieves a 14.64% improvement over MAML on the BCHI dataset and a 6.04% improvement on the PathoIDCG 40X dataset when meta-trained with the BreaKHis 40X dataset in the 3-way 5-shot scenario.

Copy number alterations in metastatic and early breast tumours: prognostic and acquired biomarkers of resistance to CDK4/6 inhibitors

BackgroundCopy number alterations (CNA) are acquired during the evolution of cancers from their early stage to metastatic stage. This study aims at analysing the clinical value of the identified metastasis-associated CNAs both in metastatic breast cancers (mBCs) and early breast cancers (eBCs).MethodsSingle-nucleotide polymorphism (SNP)-array was performed on 926 biopsies from mBC patients, enrolled in SAFIR02-BREAST prospective trial. CNA profiles of eBCs from The Cancer Genome Atlas Breast Invasive Carcinoma (n = 770), Molecular Taxonomy of Breast Cancer International Consortium (n = 1620) and PACS04 trial (n = 243) cohorts were used as references for comparing mBCs and eBCs CNA profiles. Overall survival was the considered survival endpoint.ResultsAmong the twenty-one genes frequently altered in ER + /HER2− mBCs: focal amplification of TERT was associated with poor outcome in the ER + /HER2− mBC population. Among the ER + /HER2− mBCs patients for whom CDK4/6 inhibitors information before biopsies collection was available: we identified seven genes on post-treatment biopsies, including the cyclin-dependent kinase 4 (CDK4), which was amplified in 9.8% of the ER + /HER2− mBCs pretreated population, as compared to 1.5% in the ER + /HER2− mBCs unpretreated population (P = 2.82E-04) as well as the 3 eBC populations. CDK4 amplification was associated with poor outcome in the ER + /HER2− eBCs.ConclusionsThis study provides insights into the biology of mBCs and identifies clinically useful genomic features for future improvement of breast cancer patient management.

Bioinformatic Analysis Reveals Bone Marrow Kinase as a Potential Diagnostic and Prognostic Biomarker for Multiple Cancer Types.

Bone marrow kinase, or BMX, is alternatively referred to as endothelial tyrosine kinase (Etk). It plays a vital role in the processes of cell proliferation, survival, immune activation, and the modulation of diverse signaling pathways. Since there are few direct comprehensive studies linkingBMX role with multiple cancers, this study aimed to utilize bioinformatic tools to conduct a comprehensive analysis of BMX across multiple cancers, assessing its potential role. Multiple databases including the Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), and University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN), have been used to explore BMX expression across different cancers, which has been further validated by using Gene Expression Omnibus (GEO) public datasets. In addition, we used the Kaplan-Meier plotter to estimate overall survival and cBioPortal for genetic alterations analysis. This study accommodates several other analyses like clinical parameters, immune cell infiltration, and DNA promoter methylation profiles to evaluate the general role of BMXin several cancers. Results: The present investigation revealed that the BMX gene expression was significantly downregulated and could serve as an effective diagnostic biomarker in five types of cancers, namely breast invasive carcinoma (BRCA), colon adenocarcinoma (COAD), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and rectum adenocarcinoma (READ) (all p < 0.05). Detailed analyses revealed notable downregulation of BMX in various clinical parameters such as age, gender, race, and cancer stage (all p < 0.05). To better understand the immunotherapeutic role of BMX, this investigation further examined the immune infiltration which exhibited positive correlations between BMX expression and the infiltration of immunological cells such as B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells, especially in COAD, LUAD, and LUSC(all p < 0.05).In addition, the present study has demonstrated that diminished BMX gene expression is correlated with an unfavorable prognosis in kidney renal clear cell carcinoma (KIRC), liver hepatocellular carcinoma (LIHC), sarcoma (SARC), and uterine corpus endometrial carcinoma (UCEC); thus BMX gene expression can be used as a prognostic target for these specific cancers. Also, the results showed that the promoter methylation level of BMX was significantly elevated in LUAD and LUSC, whereas it was significantly decreased in BRCA (all p < 0.001). Importantly, our findings of significantly low BMX expression inLUAD and LUSC, along with their methylation profiles suggest that the low expression of BMX across these cancers is due to epigenetic factors. However, genetic alteration analysis revealed that mutations existed in only approximately 2% of the TCGA samples. Our study revealed BMX as a diagnostic biomarker in BRCA, COAD, LUAD, LUSC, and READ and a prognostic biomarker in KIRC, LIHC, SARC, and UCEC. Furthermore, epigenetic variables may have a greater impact on BMX expression levels especially in LUAD and LUSC. This study also emphasized the role of BMX in the infiltration of immune cells, such as B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells, in certain cancers. The BMX expression level highlights the prognostic value and potential therapeutic potential of BMX.

CNN-based deep learning approach for classification of invasive ductal and metastasis types of breast carcinoma.

Breast cancer is one of the leading cancer causes among women worldwide. It can be classified as invasive ductal carcinoma (IDC) or metastatic cancer. Early detection of breast cancer is challenging due to the lack of early warning signs. Generally, a mammogram is recommended by specialists for screening. Existing approaches are not accurate enough for real-time diagnostic applications and thus require better and smarter cancer diagnostic approaches. This study aims to develop a customized machine-learning framework that will give more accurate predictions for IDC and metastasis cancer classification. This work proposes a convolutional neural network (CNN) model for classifying IDC and metastatic breast cancer. The study utilized a large-scale dataset of microscopic histopathological images to automatically perceive a hierarchical manner of learning and understanding. It is evident that using machine learning techniques significantly (15%-25%) boost the effectiveness of determining cancer vulnerability, malignancy, and demise. The results demonstrate an excellent performance ensuring an average of 95% accuracy in classifying metastatic cells against benign ones and 89% accuracy was obtained in terms of detecting IDC. The results suggest that the proposed model improves classification accuracy. Therefore, it could be applied effectively in classifying IDC and metastatic cancer in comparison to other state-of-the-art models.

A newly Diagnosed Female Breast Cancer in Karbala: Demographic, Clinical, and Histopathological Characteristics

Abstract: Background: Breast cancer is considered as a significant public health issue due to its high incidence, prevalence, and mortality rate. It is a multi - faceted disease with both environmental and genetic causal factors. It is the first of the 10 most popular tumors triggering public concern in Iraq, compensating for 20% of all cancers and approximately 33 percent of total of female cancers. Materials and methods: This retrospective study was accomplished at the Breast Clinic, Al-Hussein Teaching Medical City, Karbala province, Iraq from September 2020 to March 2021. The study enrolled a randomly selected group of women (70 patients) newly diagnosed as breast cancer. The study included all women attending the breast clinic diagnosed a breast cancer based on clinical examination in combination with positive imaging findings and confirmed by pathological assessment. The data was collected for those patients including; demographical, clinical and histopathological findings and were statistically analyzed. Results: The mean age at time of diagnosis was (52.24±10.52) years and the mean body mass index was (26.80±4.23 kg/m2). A family history of breast cancer was recorded in (21.4%) of patients. most patient were presented with painless palpable mass (74.3%). Stage II breast cancer was the most frequent stage and invasive ductal carcinoma was the most common histological type (74.3%). Most cases were expressed positive for both estrogen and progesterone receptors while was negative in (84.3%) for human epidermal growth factor receptor 2. Conclusion: a significant proportion of breast cancer patients in Iraq have locally advanced disease with the most common complaint being a painless breast lump at time of diagnosis. Key words: breast cancer, invasive ductal carcinoma, immunohistochemistry.

Evaluation of the intramammary distribution of breast lesions detected by MRI but not conventional second-look B-mode ultrasound using an MRI/ultrasound fusion technique

The objective of this study was to evaluate the intramammary distribution of MRI-detected mass and focus lesions that were difficult to identify with conventional B-mode ultrasound (US) alone. Consecutive patients with lesions detected with MRI but not second-look conventional B-mode US were enrolled between May 2015 and June 2023. Following an additional supine MRI examination, we performed third-look US using real-time virtual sonography (RVS), an MRI/US image fusion technique. We divided the distribution of MRI-detected mammary gland lesions as follows: center of the mammary gland versus other (superficial fascia, deep fascia, and atrophic mammary gland). We were able to detect 27 (84%) of 32 MRI-detected lesions using third-look US with RVS. Of these 27 lesions, 5 (19%) were in the center of the mammary gland and 22 (81%) were located in other areas. We were able to biopsy all 27 lesions; 8 (30%) were malignant and 19 (70%) were benign. Histopathologically, three malignant lesions were invasive ductal carcinoma (IDC; luminal A), one was IDC (luminal B), and four were ductal carcinoma in situ (low-grade). Malignant lesions were found in all areas. During this study period, 132 MRI-detected lesions were identified and 43 (33%) were located in the center of the mammary gland and 87 (64%) were in other areas. Also, we were able to detect 105 of 137 MRI-detected lesions by second-look conventional-B mode US and 38 (36%) were located in the center of the mammary gland and 67 (64%) were in other areas. In this study, 81% of the lesions identified using third-look US with RVS and 64% lesions detected by second-look conventional-B mode US were located outside the center of the mammary gland. We consider that adequate attention should be paid to the whole mammary gland when we perform third-look US using MRI/US fusion technique.

The Pathological Pattern of Breast Cancer in the Najran Region of Saudi Arabia: A Retrospective Study.

Background Breast cancer (BC) is the most widespread cancer on a global scale, and its prevalence is likewise significant in the Kingdom of Saudi Arabia. Nevertheless, the data accessible regarding the epidemiology and histopathological characteristics of BC in clinical practice is restricted and primarily confined to research endeavors. Aim This study aims to investigate the histopathological profile of women diagnosed with BC seeking treatment at King Khalid Hospital in the Najran region of the Kingdom of Saudi Arabia. Methods In this retrospective study, BC biopsies performed on Saudi patients at King Khalid Hospital between January 2018 and December 2022 were examined. All records of breast biopsies from this timeframe were extracted from the hospital's histopathology laboratory computer database after written permission from the head of the laboratory department. For all neoplastic lesions, the World Health Organization's 2012 categorization of breast tumors was applied. Results A total of 61 women with BC were included. Women's age ranged from 30 to 89 years, with a mean age of 49.6 ± 12.3 years. The most reported BC was invasive ductal carcinoma (IDC; 70.5%). Other types reported included invasive papillary carcinoma (8.2%), ductal carcinoma in situ (4.9%), and invasive lobular carcinoma (3.3%). A total of 14 (23%) of the study women had multifocal cancer. Ki-67 was high in 19 cases (31.1%); six (9.8%) had BRCA1 mutations, and six (9.8%) had BRCA2 mutations. Conclusion The current study revealed that BC was frequent among young females, mainly IDC, which was reported on both sides at different sizes and grades. Breast lump was the most commonly presented symptom and had a high representation in women with hormonal receptors, mainly estrogen receptors, but positive genetic testing was infrequent.

Is it time to de-escalate axillary surgery in patients with ductal carcinoma in-situ undergoing mastectomy?

IntroductionAxillary surgery has been de-escalated in invasive breast carcinoma and may be omitted in certain age groups. Up to 10–20 % of patients with ductal carcinoma in-situ (DCIS) will have an element of invasion. Therefore, SLNB is indicated to rule out nodal metastasis. Our purpose was to identify the rate and possible risk factors for lymph node metastasis in DCIS, and to measure oncological outcome of positive SLNB in this group. MethodsA retrospective analysis was performed on 113 female patients with DCIS, who underwent mastectomy and SLNB. Their clinical and radiological features, as well as pre and post-operative histopathological characteristics were evaluated and data was reported over an average follow up period of 48 months. ResultDCIS was upgraded to invasive cancer in 11 patients out of 113 (9.7 %). Five patients had positive SLNB (4.4 %), one micro-metastasis (0.8 %) and four macro-metastasis (3.5 %) All the five underwent axillary lymph node dissection (ALND) and all additional nodes retrieved were negative. High nuclear grade, Her2 neu overexpression, and palpable mass showed higher odds of association with metastasis to sentinel nodes. However, due to the low event rate, the association did not reach statistical significance. Seven patients (6.2 %) developed lymphedema, 4 of which after SLNB only. No regional recurrence was reported among our study sample. ConclusionThis study confirms the very low rate of positive SLNB in patients with DCIS. It is time to de-escalate axillary surgery for patients with DCIS undergoing mastectomy and consider delayed SLNB for high risk group of patients.

71949 - Melatonin MT1 Receptor Expression in Luminal Invasive Ductal Breast Carcinoma in Postmenopausal Women

71949 - Melatonin MT1 Receptor Expression in Luminal Invasive Ductal Breast Carcinoma in Postmenopausal Women

SHG Fiberscopy Assessment of Collagen Morphology and Its Potential for Breast Cancer Optical Histology.

This study is to investigate the feasibility of our recently developed nonlinear fiberscope for label-free in situ breast tumor detection and lymph node status assessment based on second harmonic generation (SHG) imaging of fibrillar collagen matrix with histological details. The long-term goal is to improve the current biopsy-based cancer paradigm with reduced sampling errors. In this pilot study we undertook retrospective SHG imaging study of ex vivo invasive ductal carcinoma human biopsy tissue samples, and carried out quantitative image analysis to search for collagen structural signatures that are associated with the malignance of breast cancer. SHG fiberscopy image-based quantitative assessment of collagen fiber morphology reveals that: 1) cancerous tissues contain generally less extracellular collagen fibers compared with tumor-adjacent normal tissues, and 2) collagen fibers in lymph node positive biopsies are more aligned than lymph node negative counterparts. The results demonstrate the promising potential of our SHG fiberscope for in situ breast tumor detection and lymph node involvement assessment and for offering real-time guidance during ongoing tissue biopsy.

GSFM: A genome-scale functional module transformation to represent drug efficacy for in silico drug discovery

Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RSGSFM and drug efficacy, suggesting that RSGSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

RARE PRESENTATION: SYNCHRONOUS PRIMARY BREAST AND THYROID CANCER IN AN ELDERLY MALE

Synchronous primary breast and thyroid carcinomas are exceptionally rare, especially in males. This case report presents the first documented instance of synchronous primary breast and thyroid carcinoma in an 89-year-old male. The patient had a right breast mass, cervical lymph nodes and a heterogeneously enhancing lesion in right lobe of thyroid. The histopathological examination confirmed infiltrating ductal carcinoma and metastasis of papillary carcinoma thyroid in cervical lymph node. While hormonal imbalances and genetic mutations have been implicated in synchronous breast and thyroid carcinomas in females, this case underscores the complexity of cancer development and the need for additional research into the factors influencing these rare synchronous malignancies in males.

Primary Small Cell Carcinoma of the Breast Combined with Invasive Ductal Carcinoma 1

Primary small cell carcinoma of the breast (SmCC) is a rare type of breast cancer and a histological subtype of neuroendocrine breast cancer. There is no standard treatment method, and the prognosis is unknown. It needs to be differentiated from lung metastases. A case of a 52-year-old woman is reported here who was diagnosed with small cell carcinoma combined with invasive ductal carcinoma. Whole-body PET-CT and enhanced MRI of the adrenal glands excluded any other primary disease. The patient received an adjuvant chemotherapy regimen of anthracycline combined with cyclophosphamide, sequential cisplatin, and paclitaxel. The patient was kept under close observation for any changes. This case report reviews the literature on SmCC to better understand its pathology characteristics and therapy. Due to the particularity of the patient's tumour composition, we referred to the treatment plan for small-cell lung cancer and adopted a treatment plan based on cisplatin.

Special Types of Breast Cancer: Clinical Behavior and Radiological Appearance.

Breast cancer is a complex disease that includes entities with different characteristics, behaviors, and responses to treatment. Breast cancers are categorized into subgroups based on histological type and grade, and these subgroups affect clinical presentation and oncological outcomes. The subgroup of "special types" encompasses all those breast cancers with insufficient features to belong to the subgroup "invasive ductal carcinoma not otherwise specified". These cancers account for around 25% of all cases, some of them having a relatively good prognosis despite high histological grade. The purpose of this paper is to review and illustrate the radiological appearance of each special type, highlighting insights and pitfalls to guide breast radiologists in their routine work.

Association of XRCC2 with breast cancer, a multi-omics analysis at genomic, transcriptomic, and epigenomic level.

One of the main causes of cancer-related mortality for women worldwide is breast cancer (BC). The XRCC2 gene, essential for DNA repair, has been implicated in cancer susceptibility. This study aims to evaluate the association between XRCC2 and BC risk. The study was conducted at Zheen International Hospital in Erbil, Iraq, between 2021 and 2024 with a total of 88 samples, including 44 paired normal and cancer tissue samples. Mutation analysis was performed using Next-Generation Sequencing, coupled with in silico tools for variant impact prediction. Expression levels were assessed through RT-PCR, and methylation status was determined using methylation-sensitive restriction enzyme digestion PCR. The study identified seven inherited germline variants in the XRCC2 gene, with five of these mutations being Uncertain Significance, one being Likely Pathogenic, and one being Likely benign. RNA purity was found high with mean A260/280 ratios of 1.986 ± 0.097 in normal (N) and 1.963 ± 0.092 in tumor (T) samples. Tumor samples exhibited a higher RNA concentration (78.56 ± 40.87 ng/µL) than normal samples (71.44 ± 40.79 ng/µL). XRCC2 gene expression was significantly upregulated in tumor tissue, with marked increases in patients aged 40-55 and >56 years and in higher cancer grades (II and III) and invasive ductal carcinoma (p-values ranging from <0.0001 to 0.0392). DNA methylation rates in tumor tissues were low (7%), suggesting limited regulation by methylation. The study suggests that XRCC2 can be classified as an oncogene and that its structural investigation by targeted NGS and expression evaluation can be used as a potential biomarker in BC.

Urinary microRNA-210-3p as a novel and non-invasive biomarker for the detection of pancreatic cancer, including intraductal papillary mucinous carcinoma

BackgroundThis study aims to explore novel microRNAs in urine for screening and predicting clinical characteristics in pancreatic cancer (PC) patients using a microRNA array-based approach.MethodsWe used the Toray® 3D-Gene microRNA array-based approach to compare urinary levels between PC patients and healthy volunteers.Results(1) Four oncogenic microRNAs (miR-744-5p, miR-572, miR-210-3p, and miR-575) that were highly upregulated in the urine of PC patients compared to healthy individuals were identified by comprehensive microRNA array analysis. (2) Test-scale analysis by quantitative RT-PCR for each group of 20 cases showed that miR-210-3p was significantly upregulated in the urine of PC patients compared to healthy individuals (P = 0.009). (3) Validation analysis (58 PC patients and 35 healthy individuals) confirmed that miR-210-3p was significantly upregulated in the urine of PC patients compared to healthy individuals (P < 0.001, area under the receiver operating characteristic curve = 0.79, sensitivity: 0.828, specificity: 0.743). We differentiated PC patients into invasive ductal carcinoma (IDCa) and intraductal papillary mucinous carcinoma (IPMC) groups. In addition to urinary miR-210-3p levels being upregulated in IDCa over healthy individuals (P = 0.009), urinary miR-210-3p levels were also elevated in IPMC over healthy individuals (P = 0.0018). Urinary miR-210-3p can differentiate IPMC from healthy individuals by a cutoff of 8.02 with an AUC value of 0.762, sensitivity of 94%, and specificity of 63%. (4) To test whether urinary miR210-3p levels reflected plasma miR-210-3p levels, we examined the correlation between urinary and plasma levels. Spearman’s correlation analysis showed a moderate positive correlation (ρ = 0.64, P = 0.005) between miR-210-3p expression in plasma and urine.ConclusionsUrinary miR-210-3p is a promising, non-invasive diagnostic biomarker of PC, including IPMC.Trial registrationNot applicable.