Unraveling malignant phenotype of peritumoral tissue: transcriptomic insights into early-stage breast cancer.

BACKGROUND: Early-stage invasive ductal carcinoma displays high survival rates due to early detection and treatments. However, there is still a chance of relapse of 3-15% after treatment. The aim of this study was to uncover the distinctive transcriptomic characteristics and monitoring prognosis potential of peritumoral tissue in early-stage cases. METHODS: RNA was isolated from tumoral, peritumoral, and non-tumoral breast tissue from surgical resection of 10 luminal early-stage invasive ductal carcinoma patients. Transcriptome expression profiling for differentially expressed genes (DEGs) identification was carried out through microarray analysis. Gene Ontology and KEGG pathways enrichment analysis were explored for functional characterization of identified DEGs. Protein-Protein Interactions (PPI) networks analysis was performed to identify hub nodes of peritumoral tissue alterations and correlated with Overall Survival and Relapse Free Survival. RESULTS: DEGs closely related with cell migration, extracellular matrix organization, and cell cycle were upregulated in peritumoral tissue compared to non-tumoral. Analyzing PPI networks, we observed that the proximity to tumor leads to the alteration of gene modules involved in cell proliferation and differentiation signaling pathways. In fact, in the peritumoral area were identified the top ten upregulated hub nodes including CDK1, ESR1, NOP58, PCNA, EZH2, PPP1CA, BUB1, TGFBR1, CXCR4, and CCND1. A signature performed by four of these hub nodes (CDK1, PCNA, EZH2, and BUB1) was associated with relapse events in untreated luminal breast cancer patients. CONCLUSIONS: In conclusion, our study characterizes in depth breast peritumoral tissue providing clues on the changes that tumor signaling could cause in patients with early-stage breast cancer. We propose that the use of a four gene signature could help to predict local relapse. Overall, our results highlight the value of peritumoral tissue as a potential source of new biomarkers for early detection of relapse and improvement in invasive ductal carcinoma patient's prognosis.

The VISTA/VSIG3/PSGL-1 axis: crosstalk between immune effector cells and cancer cells in invasive ductal breast carcinoma.

A checkpoint protein called the V-domain Ig suppressor of T cell activation (VISTA) is important for controlling immune responses. Immune cells that interact with VISTA have molecules, or receptors, known as VISTA receptors. Immune system activity can be modified by the interaction between VISTA and its receptors. Since targeting VISTA or its receptors may be beneficial in certain conditions, VISTA has been studied in relation to immunotherapy for cancer and autoimmune illnesses. The purpose of this study was to examine the expression levels and interactions between VISTA and its receptors, VSIG3 and PSGL-1, in breast cancer tissues. IHC analysis revealed higher levels of proteins within the VISTA/VSIG3/PSGL-1 axis in cancer tissues than in the reference samples (mastopathies). VISTA was found in breast cancer cells and intratumoral immune cells, with membranous and cytoplasmic staining patterns. VISTA was also linked with pathological grade and VSIG3 and PSGL-1 levels. Furthermore, we discovered that the knockdown of one axis member boosted the expression of the other partners. This highlights the significance of VISTA/VSIG3/PSGL-1 in tumor stroma and microenvironment remodeling. Our findings indicate the importance of the VISTA/VSIG3/PSGL-1 axis in the molecular biology of cancer cells and the immune microenvironment.

Characterization and classification of ductal carcinoma tissue using four channel based stokes-mueller polarimetry and machine learning.

Interaction of polarized light with healthy and abnormal regions of tissue reveals structural information associated with its pathological condition. Even a slight variation in structural alignment can induce a change in polarization property, which can play a crucial role in the early detection of abnormal tissue morphology. We propose a transmission-based Stokes-Mueller microscope for quantitative analysis of the microstructural properties of the tissue specimen. The Stokes-Mueller based polarization microscopy provides significant structural information of tissue through various polarization parameters such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP), anisotropy (r) and Mueller decomposition parameters such as diattenuation, retardance and depolarization. Further, by applying a suitable image processing technique such as Machine learning (ML) output images were analysed effectively. The support vector machine image classification model achieved 95.78% validation accuracy and 94.81% testing accuracy with polarization parameter dataset. The study's findings demonstrate the potential of Stokes-Mueller polarimetry in tissue characterization and diagnosis, providing a valuable tool for biomedical applications.

The characteristics and risk factors of breast cancer patients trend distinctive regional differences: a cross-sectional study.

OBJECTIVE: To determine the characteristics and risk factors of breast cancer patients in a tertiary care setting. METHODS: The retrospective, cross-sectional study was conducted at the Sindh Institute of Urology and Transplantation, Karachi, and comprised data of all patients diagnosed with breast cancer from March 2017 to December 2021. Demographic characteristics, clinical presentation, stage of the disease and histopathological characteristics were noted. Data related to all the variables was not available in all cases. Data was analysed using SPSS 23. RESULTS: Of the 690 patients, 683(99%) were females and 7(1%) were males. The mean age at presentation was 49.3±13.5 years, while the mean duration of symptoms was 10.24±17.64) months. Most of the females were married 642(93%) and multiparous 484(70.9%), while 293(42.5%) had breastfed their children for >1 year, and 412(59.7%) had no history of contraception use. The most common stage at presentation was stage II (48.6%), and most patients had grade II 395(57.2%) invasive ductal carcinoma, with Luminal A molecular subtype noted in 287(41.6%) cases. CONCLUSIONS: The characteristics of breast cancer in the sample had certain distinctions compared to other populations. It is important to integrate all datasets and develop guidelines appropriate to Pakistani population.

Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer Predicted by CD4+, CD8+, and FOXP3+ Tumor-Infiltrating Lymphocytes.

BACKGROUND: Response to neoadjuvant chemotherapy (NC) in individuals with invasive breast cancer (IBC) must be monitored, and biomarkers are needed. NC can activate an anti-tumour immune response in its microenvironment, known as Tumor-infiltrating Lymphocytes (TIL). TIL components believed to have great potential as predictors are CD4+, CD8+, and FOXP3+ TIL. This study aims to explore TIL components that can potentially be predictive biomarkers of NC pathological responses. METHODS: A sample size of 40 were analyzed based on the relationship between CD4+, CD8+, and FOXP3+ TIL expression with the Miller-Payne (MP) grading system. Age, tumour grade, PR, ER, Ki-67, and HER2 were also evaluated. CD4+, CD8+, and FOXP3+ TIL expressions were analayzed by IHC staining, while other data were collected from archives. Data was analyzed using univariate and multivariate analysis. RESULTS: Univariate analysis showed a significant relationship between CD4+ TIL and MP (p<0.001), CD8+ and MP (p=0.004), and FOXP3 with MP (p<0.001). The simultaneous integration of the three biomarkers in one model was not good enough to be a predictive model. Therefore, an exploratory analysis was conducted by testing several alternative models that combined two of the three existing biomarkers. It turned out that CD4+ TIL in model 2 (CD4+CD8+) and FOXP3+ TIL in model 4 (CD8+FOXP3+) showed significant coefficient values. Moreover, all of the threshold coefficients in model 4 are significant. CONCLUSION: This study shows that CD4+, CD8+, and FOXP3+ TIL have promising potential as predictive biomarkers. In particular, FOXP3+ is dominant in predictive models of pathological response in patients with IBC.

Clinicopathological Significance of Cyclin-Dependent Kinase 2 (CDK2) in Ductal Carcinoma In Situ and Early-Stage Invasive Breast Cancers.

Cyclin-dependent kinase 2 (CDK2) is a key cell cycle regulator, with essential roles during G1/S transition. The clinicopathological significance of CDK2 in ductal carcinomas in situ (DCIS) and early-stage invasive breast cancers (BCs) remains largely unknown. Here, we evaluated CDK2's protein expression in 479 BC samples and 216 DCIS specimens. Analysis of CDK2 transcripts was completed in the METABRIC cohort (n = 1980) and TCGA cohort (n = 1090), respectively. A high nuclear CDK2 protein expression was significantly associated with aggressive phenotypes, including a high tumour grade, lymph vascular invasion, a poor Nottingham prognostic index (all p-values < 0.0001), and shorter survival (p = 0.006), especially in luminal BC (p = 0.009). In p53-mutant BC, high nuclear CDK2 remained linked with worse survival (p = 0.01). In DCIS, high nuclear/low cytoplasmic co-expression showed significant association with a high tumour grade (p = 0.043), triple-negative and HER2-enriched molecular subtypes (p = 0.01), Comedo necrosis (p = 0.024), negative ER status (p = 0.004), negative PR status (p < 0.0001), and a high proliferation index (p < 0.0001). Tumours with high CDK2 transcripts were more likely to have higher expressions of genes involved in the cell cycle, homologous recombination, and p53 signaling. We provide compelling evidence that high CDK2 is a feature of aggressive breast cancers. The clinical evaluation of CDK2 inhibitors in early-stage BC patients will have a clinical impact.

Post-surgery statin use contributes to favorable outcomes in patients with early breast cancer.

BACKGROUND: Statins are a group of lipid-lowering drugs with pleiotropic effects that include, but are not limited to the inhibition of cholesterol synthesis resulting in a wide range of anti-inflammatory, anti-tumor, immunomodulatory, and anti-thrombotic properties. This study aimed to determine the impact of the prior to- or after- breast surgery usage of statins on the tumor prognosis in breast cancer (BC) patients. METHODS: A cohort of patients diagnosed with early invasive ductal BC (n=301) at the Hospital Italiano de Buenos Aires, Argentina, with a minimum follow-up period of 10 years after the surgical procedure were included and stratified according to the time of use of statins and type of statin used. Then, local relapse-free survival (RFS), metastasis-free survival (MFS), bone metastasis-free survival (BMFS), visceral metastasis-free (VMFS), mixed metastasis (bone and visceral)-free survival (mix-MFS) and overall survival (OS) were analyzed. RESULTS: Statins usage after breast surgery was related with lesser metastatic occurrence (p=0.017), lower number of metastatic foci (p=0.034) and fewer dead events (p=0.041), as well as longer MFS (p=0.013) and OS (p=0.027). When stratified by the nature of statins (hydrophilic or lipophilic), only the relatively hydrophilic statin rosuvastatin (ROSU) had an impact on the increase of MFS and OS (p=0.018 and p=0.030, respectively). CONCLUSION: Post-surgery statins usage was associated with increased MFS and OS, with increased benefits of ROSU over simvastatin (SIM) or atorvastatin (ATOR). These results set the rationale for additional studies addressing the use of statins, and particularly, rosuvastatin, to improve the outcome of BC patients.

Breast Cancer in Younger and Older Women: A Comparison of Clinicopathological Traits.

Breast cancer stands as the prevailing invasive cancer globally, bearing high mortality rates among women. Existing evidence indicates diminished survival rates in younger patients. Consequently, this study endeavors to assess and contrast the pathological features of breast cancer in women under 40 years of age with their older counterparts. Conducted as a cross-sectional analysis, this study encompasses 560 patients diagnosed with breast cancer, seeking treatment at Mymensingh Medical College Hospital (MMCH), Community Based Medical College Bangladesh (CBMCB) and several private hospitals in Mymensingh. The gathered data incorporates information such as age, residential area, occupation, tumor histopathology, TNM classification, staging and status of hormone receptor. The patients' mean age (standard deviation) was 49.7±11.9 years, with 20.5% below 40, most were from rural areas and were housewives. Ductal carcinoma prevailed as the most common histopathologic type (87.67%). However, younger patients exhibited a higher prevalence of lobular and other rare carcinomas compared to their older counterparts (p=0.04). Additionally, the younger group demonstrated larger tumor sizes (p=0.01), lymphatic node involvement (p=0.04) and advanced staging (p=0.004). Notably, younger age showed more negativity for estrogen and/or progesterone receptors. The results suggested that women under 40 years old exhibit more aggressive tumor characteristics and a more severe form of breast cancer compared to their older counterparts.

Correlation between sentinel lymph node biopsy and non-sentinel lymph node metastasis in patients with cN0 breast carcinoma: comparison of invasive ductal carcinoma and invasive lobular carcinoma.

BACKGROUND: Some studies have suggested that axillary lymph node dissection (ALND) can be avoided in women with cN0 breast cancer with 1-2 positive sentinel nodes (SLNs). However, these studies included only a few patients with invasive lobular carcinoma (ILC), so the validity of omitting ALDN in these patients remains controversial. This study compared the frequency of non-sentinel lymph nodes (non-SLNs) metastases in ILC and invasive ductal carcinoma (IDC). MATERIALS METHODS: Data relating to a total of 2583 patients with infiltrating breast carcinoma operated at our institution between 2012 and 2023 were retrospectively analyzed: 2242 (86.8%) with IDC and 341 (13.2%) with ILC. We compared the incidence of metastasis to SLNs and non-SLNs between the ILC and IDC cohorts and examined factors that influenced non-SLNs metastasis. RESULTS: SLN biopsies were performed in 315 patients with ILC and 2018 patients with IDC. Metastases to the SLNs were found in 78/315 (24.8%) patients with ILC and in 460 (22.8%) patients with IDC (p = 0.31). The incidence of metastases to non-SLNs was significantly higher (p = 0.02) in ILC (52/78-66.7%) compared to IDC (207/460 - 45%). Multivariate analysis showed that ILC was the most influential predictive factor in predicting the presence of metastasis to non-SLNs. CONCLUSIONS: ILC cases have more non-SLNs metastases than IDC cases in SLN-positive patients. The ILC is essential for predicting non-SLN positivity in macro-metastases in the SLN. The option of omitting ALND in patients with ILC with 1-2 positive SLNs still requires further investigation.

[A Long-Surviving Case of Locally Advanced Breast Cancer with Multiple Lung Metastasis].

We report a case of right advanced breast cancer with multiple lung metastases in a 66-year-old woman. Her breast cancer( invasive ductal carcinoma, cT4bN1M1, Stage Ⅳ)was resected in October 2007(mastectomy plus axillary lymph node dissection)after local arterial infusion therapy(total dose 5-FU 4,735 mg plus adriamycin 180 mg), which caused bilateral lung arterial embolism due to deep vein thrombosis in right her leg. She had to be treated by anticoagulant therapy, mechanical ventilation and placement of IVC filter before her operation. Subsequent chemo-endocrine therapy(docetaxel 6 courses plus anastrozole)was continued. In October 2008, a CT scan showed disappearance of multiple lung metastases (complete response). In November 2015 (8 years after her operation), a CT scan showed recurrence of multiple lung metastases and endocrine therapy was changed to tamoxifen. A year later, a CT scan showed disappearance of multiple lung metastases(complete response)again and keep a condition of complete response in her breast cancer until May 2023 (15 years after her operation).

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials. OBJECTIVE: To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance. METHODS: In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS. RESULTS: When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved. CONCLUSION: For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.

Correlation of IDH1 gene expression error in breast tumor biopsy in patients with invasive ductal carcinoma.

One of the most important cancers in terms of worldwide prevalence is breast tumors, which have been less investigated in correlation with the enzyme Isocitrate Dehydrogenase 1 (IDH1) gene. The aim of this study was that expression of this gene could have significant effects on the progression of metastasis and invasive disease in breast cancer patients. We used the molecular method of RT-PCR with SYBR-Green to analyze breast tumor tissue from patients with metastasis and non-metastasis, the latter confirmed by the pathology department of Shohada-e Tajrish Hospital (serving as a control group). Also, patients population and its relationship with the degree of tumor in the IDH1 gene was investigated. The IDH1 gene has shown high expression in patients with metastatic breast cancer rather than in patients with non-metastatic breast cancer. The metastatic samples were compared with non-metastatic samples for IDH1 mRNA expression. In this research work, 72.5% (29 samples) were up-regulated in comparison to 27.5% of samples (11 samples) that did not exhibit high expression (P=0.000).  This study examined the IDH1 gene expression, suggesting that changes in this gene's expression could impact the prognosis of breast cancer. However, further research is needed to draw definitive conclusions.

Intra and peritumoral PET radiomics analysis to predict the pathological response in breast cancer patients receiving neoadjuvant chemotherapy.

OBJECTIVE: The aim of our study was to evaluate the contribution of 18Fluorine-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) radiomic data obtained from both the tumoral and peritumoral area in predicting pathological complete response (pCR) in patients with locally advanced breast cancer receiving neoadjuvant chemotherapy (NAC). METHODS: Female patients with a diagnosis of invasive ductal carcinoma who received NAC were evaluated retrospectively. The volume of interest (VOI) of the primary tumor (VOI-T) was manually segmented, then a voxel-thick VOI was added around VOI-T to define the peritumoral area (VOI-PT). Morphological, intensity-based, histogram and texture parameters were obtained from VOIs. The patients were divided into two groups as pCR and non-complete pathological response (npCR). A "radiomic model" was created with only radiomic features, and a "patho-radiomic model" was created using radiomic features and immunohistochemical data. RESULTS: Of the 66 patients included in the study, 21 were in the pCR group. The only statistically significant feature from the primary tumor among patients with pCR and npCR was Morphological_Compacity-T (AUC: 0.666). Between response groups, a significant difference was detected in 2 morphological, 1 intensity, 4 texture features from VOI-PT; no correlation was found between Morphological_Compacity-PT and NGTDM_contrast-PT. The obtained radiomic model's sensitivity and accuracy values were calculated as 61.9% and 75.8%, respectively (AUC: 0.786). When HER2 status was added, sensitivity and accuracy values of the patho-radiomic model increased to 85.7% and 81.8%, respectively (AUC: 0.903). CONCLUSIONS: Evaluation of PET peritumoral radiomic features together with the primary tumor, rather than just the primary tumor, provides a better prediction of the pCR to NAC in patients with breast cancer.

Male ductal carcinoma in situ: diagnosis and management of a rare disease in men.

Ductal carcinoma in situ is very rare in male patients, accounting for approximately 5%-7% of all male breast cancers. We present a case of a man in his early 70s who presented with bloody nipple discharge and gynaecomastia and was subsequently diagnosed with ductal carcinoma in situ (DCIS). We discuss his management with surgical resection and the consideration of adjuvant treatment. We also review the existing literature on the presentation, diagnosis and management of DCIS in men.

Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer.

PURPOSE: The progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) in humans is highly variable. To better understand the relationship between them, we performed a multi-omic characterization of co-occurring DCIS and IBC lesions in a cohort of individuals. METHODS: Formalin-fixed paraffin-embedded tissue samples from 50 patients with co-occurring DCIS and IBC lesions were subjected to DNA-seq and whole transcriptome RNA-seq. Paired DCIS and IBC multi-omics profiles were then interrogated for DNA mutations, gene expression profiles and pathway analysis. RESULTS: Most small variants and copy number variations were shared between co-occurring DCIS and IBC lesions, with IBC exhibiting on average a higher degree of additional mutations. However, 36% of co-occurring lesions shared no common mutations and 49% shared no common copy number variations. The most frequent genomic variants in both DCIS and IBC were PIK3CA, TP53, KMT2C, MAP3K1, GATA3 and SF3B1, with KMT2C being more frequent in DCIS and TP53 and MAP3K1 more frequent in IBC, though the numbers are too small for definitive conclusions. The most frequent copy number variations were seen in MCL1, CKSB1 and ERBB2. ERBB2 changes were not seen in IBC unless present in the corresponding DCIS. Transcriptional profiles were highly distinct between DCIS and IBC, with DCIS exhibiting upregulation of immune-related signatures, while IBC showed significant overexpression in genes and pathways associated with cell division and proliferation. Interestingly, DCIS and IBC exhibited significant differential expression of different components of extracellular matrix (ECM) formation and regulation, with DCIS showing overexpression of ECM-membrane interaction components while IBC showed upregulation of genes associated with fibronectin and invadopodia. CONCLUSION: While most co-occurring DCIS and IBC were mutationally similar and suggestive of a common clonal progenitor, transcriptionally the lesions are highly distinct, with IBC expressing key pathways that facilitate invasion and proliferation. These results are suggestive of additional levels of regulation, epigenetic or other, that facilitate the acquisition of invasive properties during tumor evolution.

Clinicopathological Predictors of Positive Resection Margins in Breast-Conserving Surgery.

BACKGROUND: Ductal carcinoma in situ (DCIS) is associated with risk of positive resection margins following breast-conserving surgery (BCS) and subsequent reoperation. Prior reports grossly underestimate the risk of margin positivity with IBC containing a DCIS component (IBC + DCIS) due to patient-level rather than margin-level analysis. OBJECTIVE: The aim of this study was to delineate the relative risk of IBC + DCIS compared with pure IBC (without a DCIS component) on margin positivity through detailed margin-level interrogation. METHODS: A single institution, retrospective, observational cohort study was conducted in which pathology databases were evaluated to identify patients who underwent BCS over 5 years (2014-2019). Margin-level interrogation included granular detail into the extent, pathological subtype and grade of disease at each resection margin. Predictors of a positive margin were computed using multivariate regression analysis. RESULTS: Clinicopathological details were examined from 5454 margins from 909 women. The relative risk of a positive margin with IBC + DCIS versus pure IBC was 8.76 (95% confidence interval [CI] 6.64-11.56) applying UK Association of Breast Surgery guidelines, and 8.44 (95% CI 6.57-10.84) applying the Society of Surgical Oncology/American Society for Radiation Oncology guidelines. Independent predictors of margin positivity included younger patient age (0.033, 95% CI 0.006-0.060), lower specimen weight (0.045, 95% CI 0.020-0.069), multifocality (0.256, 95% CI 0.137-0.376), lymphovascular invasion (0.138, 95% CI 0.068-0.208) and comedonecrosis (0.113, 95% CI 0.040-0.185). CONCLUSIONS: Compared with pure IBC, the relative risk of a positive margin with IBC + DCIS is approximately ninefold, significantly higher than prior estimates. This margin-level methodology is believed to represent the impact of DCIS more accurately on margin positivity in IBC.