Prognostic Marker In Breast Cancer Research Articles

Clinico-pathological association of BCL2 in invasive breast carcinoma: A study from tertiary care health centre in Northern India.

B-cell lymphoma 2 (Bcl-2) is an antiapoptotic protein and an important clinical breast cancer prognostic marker. The aim of this study was to evaluate the relationship between the BCL2 expression and clinico-pathological parameters in breast cancer. Present study is observational cross-sectional study of 100 biopsy proven cases of breast cancer, and cases with resection specimens were included. IHC analyses for ER, PR, Her2neu, Ki67 and Bcl2 were performed in each case. Bcl2 expression was seen in 52% cases. BCL2-positive expression was associated with lower histological grade (0.026), low Ki-67 level (<14%, P < 0.001), hormone receptor positivity (P < 0.001) and luminal breast cancer (P < 0.001) but no association with tumour size, lymphovascular invasion, perineural invasion and TNM stage. Expression of Bcl-2, an antiapoptotic protein, is associated with low-grade, slowly proliferating, luminal A-type BC. IHC analysis of Bcl-2 is simple, inexpensive, readily available test to stratify early-stage hormone-positive patients who can be included in clinical trials for Bcl-2 inhibitors.

MRPL13 is a metastatic and prognostic marker of breast cancer: A silico analysis accompanied with experimental validation

BackgroundAlthough progress has been made in accurate diagnosis and targeted treatments, breast cancer (BC) patients with metastasis still present a grim prognosis. With the continuous emergence and development of new personalized and precision medicine targeting specific tumor biomarkers, there is an urgent need to find new metastatic and prognostic biomarkers for BC patients. MethodsWe were dedicated to identifying genes linked to metastasis and prognosis in breast cancer through a combination of in silico analysis and experimental validation. ResultsA total of 25 overlap differentially expressed genes were identified. Ten hub genes (namely MRPL13, CTR9, TCEB1, RPLP0, TIMM8B, METTL1, GOLT1B, PLK2, PARL and MANBA) were identified and confirmed. MRPL13, TCEB1 and GOLT1B were shown to be associated with the worse overall survival (OS) and were optionally chosen for further verification by western blot. Only MRPL13 was found associated with cell invasion, and the expression of MRPL13 in metastatic BC was significantly higher than in primary BC. ConclusionWe proposed MRPL13 could be a potential novel biomarker for the metastasis and prognosis of breast cancer.

FGFR‑related phenotypic and functional profile of CAFs in prognostication of breast cancer (Review).

While preclinical studies consistently implicate FGFR‑signalling in breast cancer (BC) progression, clinical evidence fails to support these findings. It may be that the clinical significance of FGFR ought to be analysed in the context of the stroma, activating or repressing its function. The present review aimed to provide such a context by summarizing the existing data on the prognostic and/or predictive value of selected cancer‑associated fibroblasts (CAFs)‑related factors, that either directly or indirectly may affect FGFR‑signalling. PubMed (https://pubmed.ncbi.nlm.nih.gov/) and Medline (https://www.nlm.nih.gov/medline/medline_home.html) databases were searched for the relevant literature related to the prognostic and/or predictive significance of: CAFs phenotypic markers (αSMA, S100A4/FSP‑1, PDGFR, PDPN and FAP), CAFs‑derived cognate FGFR ligands (FGF2, FGF5 and FGF17) or inducers of CAFs' paracrine activity (TGF‑β1, HDGF, PDGF, CXCL8, CCL5, CCL2, IL‑6, HH and EGF) both expressed in the tumour and circulating in the blood. A total of 68 articles were selected and thoroughly analysed. The findings consistently identified upregulation of αSMA, S100A4/FSP‑1, PDGFR, PDPN, HDGF, PDGF, CXCL8, CCL5, CCL2, IL‑6, HH and EGF as poor prognostic markers in BC, while evaluation of the prognostic value of the remaining markers varied between the studies. The data confirm an association of CAFs‑specific features with BC prognosis, suggesting that both quantitative and qualitative profiling of the stroma might be required for an assessment of the true FGFR's clinical value.

Role of MicroRNA-204 in Regulating the Hallmarks of Breast Cancer: An Update.

microRNA-204-5p (miR-204) is a small noncoding RNA with diverse regulatory roles in breast cancer (BC) development and progression. miR-204 is implicated in the instauration of fundamental traits acquired during the multistep development of BC, known as the hallmarks of cancer. It may act as a potent tumor suppressor by inhibiting key cellular processes like angiogenesis, vasculogenic mimicry, invasion, migration, and metastasis. It achieves this by targeting multiple master genes involved in these processes, including HIF-1α, β-catenin, VEGFA, TGFBR2, FAK, FOXA1, among others. Additionally, miR-204 modulates signaling pathways like PI3K/AKT and interacts with HOTAIR and DSCAM-AS1 lncRNAs, further influencing tumor progression. Beyond its direct effects on tumor cells, miR-204 shapes the tumor microenvironment by regulating immune cell infiltration, suppressing pro-tumorigenic cytokine production, and potentially influencing immunotherapy response. Moreover, miR-204 plays a crucial role in metabolic reprogramming by directly suppressing metabolic genes within tumor cells, indirectly affecting metabolism through exosome signaling, and remodeling metabolic flux within the tumor microenvironment. This review aims to present an update on the current knowledge regarding the role of miR-204 in the hallmarks of BC. In conclusion, miR-204 is a potential therapeutic target and prognostic marker in BC, emphasizing the need for further research to fully elucidate its complex roles in orchestrating aggressive BC behavior.

Exploring SALL4 as a significant prognostic marker in breast cancer and its association with progression pathways involved in cancer genesis

Breast carcinoma is the leading factor in women's cancer-related fatalities. Due to its numerous inherent molecular subtypes, breast cancer is an extremely diverse illness. The human epidermal growth factor receptor 2 (HER2) positive subtypes stands out among these subtypes as being especially prone to cancer development and illness recurrence. The regulation of embryonic stem cells' pluripotency and self-renewal is carried out by the SALL4 (Spalt-like transcription factor 4) family member. Numerous molecular pathways operating at the transcriptional, post-transcriptional, and epigenomic levels regulate the expression of SALL4. Many transcription factors control the expression of SALL4, with STAT3 being the primary regulator in hepatocellular carcinoma (HCC) and breast carcinoma. Moreover, this oncogene has been connected to a number of cellular functions, including invasion, apoptosis, proliferation, and resistance to therapy. Reduced patient survival rates and a worse prognosis have been linked to higher levels of SALL4. In order to target the undruggable SALL4 that is overexpressed in breast carcinoma, we investigated the prognostic levels of SALL4 in breast carcinoma and its interaction with various related proteins. Using TIMER 2.0 analysis, the expression pattern of SALL4 was investigated across all TCGA datasets. The research revealed that SALL4 expression was elevated in various cancers. The UALCAN findings demonstrated that SALL4 was overexpressed in all tumor samples including breast cancer especially TNBC (Triple negative breast cancer). The web-based ENRICHR program was used for gene ontology analysis that revealed SALL4 was actively involved in the development of the nervous system, positive regulation of stem cell proliferation, regulation of stem cell proliferation, regulation of the activin receptor signaling pathway, regulation of transcription using DNA templates, miRNA metabolic processes, and regulation of transcription by RNA Polymerase I. Using the STRING database, we analyzed the interaction and involvement of SALL4 with other abruptly activated proteins and used Cytoscape 3.8.0 for visualization. Additionally, using bc-GenExMiner, we studied the impact of SALL4 on pathways abruptly activated in different breast cancer subtypes that revealed SALL4 was highly correlated with WNT2B, NOTCH4, AKT3, and PIK3CA. Furthermore, to target SALL4, we evaluated and analyzed the impact of CLP and its analogues, revealing promising outcomes.

The potential role of collagen type VII in breast cancer proliferation

BackgroundBreast cancer is the most common cancer in women. Cancer cells can persist in a prolonged dormant state for years without any clinical evidence of disease creating an urgent need to better understand the molecular mechanisms leading to relapse. This study aimed to identify extracellular matrix (ECM) components associated with hypoxia-induced breast cancer dormancy. The effects of selected ECM proteins on breast cancer cell proliferation were analyzed, along with their correlation with established prognostic markers in human breast cancer tissue.Materials and methodsScreening of extracellular matrix proteins was performed in hypoxia-induced dormant MCF-7 breast cancer cells. Proliferation of MCF-7 cells in vitro was subsequently determined in the presence of recombinant ColVII. Adipose tissue-derived mesenchymal stem cells (AdMSCs) subpopulation overexpressing ColVII were indirectly isolated by ColVII receptor integrin-α6 specific antibodies. AdMSCs- MCF-7 3D spheroid cultures were generated to model solid tumour conditions. In addition, the association between ColVII and various prognostic markers was evaluated in clinical samples of human breast cancer tissue.ResultsDormant MCF-7 cells showed an elevated expression of ColVII while MCF-7 cells cultured on ColVII exhibited reduced proliferation in vitro. In AdMSCs-MCF-7 3D spheroids, a reduced proliferation of MCF-7 cells was observed in Int-α6+/ ColVIIhigh compared with Int-α6-/ ColVIIlow AdMSCs spheroids. In human tissue, high ColVII expression correlated to several positive prognostic markers. Staining for Cytokeratin-5 revealed that ColVIIhigh-expressing cells were predominantly myoepithelial cells.ConclusionColVII is associated with reduced proliferation of breast cancer cells in vitro. ColVII is strongly expressed in myoepithelial cells and in breast cancer tissue the high ColVII expression correlates with several well-known positive prognostic markers, highlighting its potential as a prognostic marker in breast cancer.

Prognostic value of Maspin protein level in patients with triple negative breast cancer

The search for prognostic markers in breast cancer has bumped into a typical feature of these tumors, intra and intertumoral heterogeneity. Changes in the expression profile, localization of these proteins or shedding to the surrounding stroma can be useful in the search for new markers. In this context, classification by molecular subtypes can bring perspectives for both diagnosis and screening for appropriate treatments. However, the Triple Negative (TN) subtype, which is already the one with the worst prognosis, lacks appropriate and consistent molecular markers. In this work, we analyzed 346 human breast cancer samples in tissue microarrays (TMA) from cases diagnosed with invasive breast carcinoma to assess the expression and localization pattern of Maspin and their correlation with clinical parameters. To complement our findings, we also used TCGA data to analyze the mRNA levels of these respective genes. Our data suggests that the TN subtype demonstrates a higher level of cytoplasmic Maspin compared to the other subtypes. Maspin transcript levels follow the same trend. However, TN patients with lower Maspin expression tend to have worse overall survival and free-survival metastasis rates. Finally, we used Maspin expression data to verify possible relationships with the clinicopathological information of our cohort. Our univariate analyses indicate that Maspin is related to the expression of estrogen receptor (ER) and progesterone receptor (PR). Furthermore, Maspin expression levels also showed correlation with Scarff-Bloom-Richardson (SBR) parameter, and stromal Maspin showed a relationship with lymph node involvement. Our data is not consistently robust enough to categorize Maspin as a prognostic marker. However, it does indicate a change in the expression profile within the TN subtype.

Bioinformatic Investigation of Genetic Changes in Paraoxonase Genes in Breast Cancer and Breast Cancer Subtypes.

Among women, breast cancer (BC) is the most prevalent form of cancer. Many molecular targets have been discovered for BC prognosis and treatment. However, new markers still need to be identified, as cancer pathogenesis is triggered by different mechanisms. The aim of this study was to examine the changes in the paraoxonase genes (PON1, PON2, and PON 3) involved in the pathogenesis of BC. The characteristics of the mutations were evaluated with the Cbioportal database. Kaplan-Meier Plot evaluated recurrence-free survival (RFS). The UALCAN database determined the promoter methylation. Gene expression was evaluated by GEPIA2.0 database. PON1 harbored the most mutations. There was a significant decrease in PON3 expression levels in BC samples compared with healthy samples. PON1 and PON2 expression levels did not differ between BC tissue and normal adjacent tissue. Elevated expression levels of PON1 and PON2 genes were correlated with longer RFS, whereas reduced expression of the PON2 gene showed an association with longer RFS. Moreover, the promoter regions of PON1 and PON 3 were found to be hypermethylated, while the promoter region of PON 2 was found to be hypomethylated. The PON3 promoter region was significantly hypermethylated in luminal and human epidermal growth factor receptor 2 (HER2) + BC subtypes. However, the PON3 promoter region was significantly hypomethylated in the triple negative breast cancer (TNBC) subtype. These results suggest that methylation and expression status of PON3 in BC and BC subtypes (TNBC, luminal and HER2) may indicate a poor prognosis. The PON3 gene could be a negative prognostic marker in BC. However, the results should be supported by prospective studies.

Suppressing mitochondrial inner membrane protein (IMMT) inhibits the proliferation of breast cancer cells through mitochondrial remodeling and metabolic regulation

Metabolic reprogramming is widely recognized as a hallmark of malignant tumors, and the targeting of metabolism has emerged as an appealing approach for cancer treatment. Mitochondria, as pivotal organelles, play a crucial role in the metabolic regulation of tumor cells, and their morphological and functional alterations are intricately linked to the biological characteristics of tumors. As a key regulatory subunit of mitochondria, mitochondrial inner membrane protein (IMMT), plays a vital role in degenerative diseases, but its role in tumor is almost unknown. The objective of this research was to investigate the roles that IMMT play in the development and progression of breast cancer (BC), as well as to elucidate the underlying biological mechanisms that drive these effects. In this study, it was confirmed that the expression of IMMT in BC tissues was significantly higher than that in normal tissues. The analysis of The Cancer Genome Atlas (TCGA) database revealed that IMMT can serve as an independent prognostic factor for BC patients. Additionally, verification in clinical specimens of BC demonstrated a positive association between high IMMT expression and larger tumor size (> 2 cm), Ki-67 expression (> 15%), and HER-2 status. Furthermore, in vitro experiments have substantiated that the suppression of IMMT expression resulted in a reduction in cell proliferation and alterations in mitochondrial cristae, concomitant with the liberation of cytochrome c, but it did not elicit mitochondrial apoptosis. Through Gene Set Enrichment Analysis (GSEA) analysis, we have predicted the associated metabolic genes and discovered that IMMT potentially modulates the advancement of BC through its interaction with 16 metabolic-related genes, and the changes in glycolysis related pathways have been validated in BC cell lines after IMMT inhibition. Consequently, this investigation furnishes compelling evidence supporting the classification of IMMT as prognostic marker in BC, and underscoring its prospective utility as a novel target for metabolic therapy.

Unveiling the complexity: Liquid biopsy-based proteomic exploration of triple-negative breast cancer in women.

e13138 Background: This groundbreaking study places a spotlight on breast cancer in women, with a specific emphasis on the challenging triple-negative breast cancer (TNBC) subtype. Delving into the intricate world of extracellular vesicles (EVs) from TNBC-diagnosed individuals, the research meticulously compares various conditions, including healthy controls, benign tumors, recurrent tumors, and those in remission. Employing cutting-edge techniques like liquid biopsy and LC-MS/MS, the study meticulously explores the proteomic profile of serum exosomes, aiming to pinpoint diagnostic and prognostic markers in breast cancer. Methods: In the initial phase, EVs were expertly isolated and characterized from blood plasma samples exclusively from women, utilizing state-of-the-art methods such as ultracentrifugation and nanoparticle tracking analysis (NTA). Despite applying rigorous statistical criteria, the study found no significant differences in EV concentrations and sizes among the diverse groups. However, the ensuing proteomic analysis uncovered 130 proteins, with Cystatin A and Histone H2A emerging as promising biomarkers for TNBC. To validate them, the study intricately tested tumor cell lines from distinct subtypes, representing luminal, triple-negative, and HER2 overexpressed. The examination of gene and protein expression through RT-qPCR and western blotting added a layer of depth to the research, unraveling the complexity of regulatory processes within cells and demonstrating a remarkable congruence between protein levels found in the proteomics from patients’ serum and in immortalized cell lines. Results: The proteomic analysis brought to light the absence of CSTA and HIST1H2A expression in benign tumor patients, varied levels in malignant tumor patients, and a substantial increase in TNBC patients pre-mastectomy. Validating these findings through western blotting further accentuated the potential of these proteins as distinguishing factors. Conclusions: In conclusion, this pioneering study not only underscores the immense potential of liquid biopsy-based proteomic analysis in identifying crucial diagnostic and prognostic markers in breast cancer but also sheds light on the intricate nuances of the challenging TNBC subtype. Our findings unveil valuable insights that pave the way for future personalized treatment strategies, marking a significant stride forward in breast cancer research.

Identification of SMC2 and SMC4 as prognostic markers in breast cancer through bioinformatics analysis.

Breast cancer (BRCA) is one of the most common malignant tumors. The structural maintenance of chromosome (SMC) gene family has been shown to play an important role in human cancers. However, the role of SMC families in BRCA is unclear. This study aimed to explore the role and potential clinical value of whole SMCs in BRCA. TIMER and UALCAN database were used to analysis the expression level. Genetic variations were analyzed by cBioPortal. Promoter methylation and protein level were analyzed by UCLCAN. GO and KEGG were analyzed by Metascape database. Prognostic value of SMCs was analyzed by Kaplan-Meier and multivariate cox regression analyses. Immune infiltration analysis was conducted by CIBERSORT. Immunotherapy outcome prediction was conducted by Cancer Immunome Atlas. Targeted drug therapy outcome prediction was taken by GDSC and R language. The cell viability was tested by CCK8 and migration was tested by wound healing assay. Xenograft model was used to investigate the in vivo role of SMC2. Expression levels of SMC1A, SMC2, SMC4, SMC5 and SMC6 mRNA were increased in BRCA tissues, and negatively correlated with promoter methylation. Overexpression of SMC2 and SMC4 was negatively correlated with survival. Function of SMCs family regulatory genes was mainly related to ATPase activity. Expression of most SMCs was negatively correlated with immunotherapy and drug therapy outcomes. Interfere SMC2 and SMC4 decreased IC50 values of 5-fluorouracil and oxaliplatin and inhibited the migration of MCF7 cells. Tumor growth and weights were significantly decreased in si-SMC2 groups. Combined bioinformatics and clinical specimen analysis verified SMC2 and SMC4 as independent prognostic factors in BRCA, suggesting their significance for the diagnosis and treatment of BRCA.

PMBC: a manually curated database for prognostic markers of breast cancer.

Breast cancer is notorious for its high mortality and heterogeneity, resulting in different therapeutic responses. Classical biomarkers have been identified and successfully commercially applied to predict the outcome of breast cancer patients. Accumulating biomarkers, including non-coding RNAs, have been reported as prognostic markers for breast cancer with the development of sequencing techniques. However, there are currently no databases dedicated to the curation and characterization of prognostic markers for breast cancer. Therefore, we constructed a curated database for prognostic markers of breast cancer (PMBC). PMBC consists of 1070 markers covering mRNAs, lncRNAs, miRNAs and circRNAs. These markers are enriched in various cancer- and epithelial-related functions including mitogen-activated protein kinases signaling. We mapped the prognostic markers into the ceRNA network from starBase. The lncRNA NEAT1 competes with 11 RNAs, including lncRNAs and mRNAs. The majority of the ceRNAs in ABAT belong to pseudogenes. The topology analysis of the ceRNA network reveals that known prognostic RNAs have higher closeness than random. Among all the biomarkers, prognostic lncRNAs have a higher degree, while prognostic mRNAs have significantly higher closeness than random RNAs. These results indicate that the lncRNAs play important roles in maintaining the interactions between lncRNAs and their ceRNAs, which might be used as a characteristic to prioritize prognostic lncRNAs based on the ceRNA network. PMBC renders a user-friendly interface and provides detailed information about individual prognostic markers, which will facilitate the precision treatment of breast cancer. PMBC is available at the following URL: http://www.pmbreastcancer.com/.

Abstract PO3-28-08: Triple Hormone Receptor Signatures as Novel Prognostic Markers in Breast Cancer

Abstract Background Tumor phenotype across various cancers, including breast cancer, is predominantly shaped by a synergy between genomic alterations and the cell-of-origin from which the tumor emerges. These elements collectively influence crucial aspects like tumor aggressiveness, treatment response, and patient prognosis. While existing research highlights that the cell-of-origin often leaves a lasting imprint on the molecular architecture of tumors, leveraging this information for actionable clinical insights has proven challenging. Specifically, in the realm of breast cancer, utilizing cellular ancestry signatures could be a key factor in tailoring effective therapeutic strategies and improving patient outcomes. Methods In this study, we developed a unique signature anchored in the expression levels of triple hormone receptors (THR)—namely androgen (AR), estrogen (ER), and vitamin D (VDR)—in normal breast cells. Building on this, we formulated two distinct mRNA markers, THR-50 and THR-70, aimed at categorizing breast tumors based on their THR expression profiles. These markers were rigorously validated across 65 independent breast cancer studies, involving a total of 6,679 patients, utilizing Kaplan-Meier survival curves, Cox proportional hazards models, and unsupervised clustering analyses. Results Our findings indicate that both THR-50 and THR-70 are robustly associated with overall survival and recurrence-free survival in breast cancer patients across all datasets evaluated. Importantly, these THR signatures demonstrate broad applicability across various breast cancer subtypes, grades, and treatment phases—unlike conventional prognostic markers that tend to be subtype-specific. Additionally, the THR signatures have revealed four unique patient clusters with divergent survival outcomes, three of which are ER-positive and one ER-negative. When augmented with an immune-based signature (i20), THR-70 identifies a specific ER-negative breast cancer subgroup with a highly favorable prognosis, comparable to ER-positive subtypes, as well as another ER-negative subgroup characterized by exceedingly poor survival outcomes. Conclusion The THR-based cellular ancestry signatures open a new avenue in understanding the intricacies of breast cancer biology. These signatures offer a robust and stable framework for developing other prognostic markers, thus providing an enhanced stratification of existing breast cancer categories as well as creating new classifications. Citation Format: Mohamed Omar, Chuck Harrell, Rulla Tamimi, Luigi Marchionni, Tan Ince. Triple Hormone Receptor Signatures as Novel Prognostic Markers in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-28-08.

Abstract LB392: Transformative pathomics in oncology: Harnessing FFPE tissue slide imagery for clinically relevant gene expression prediction in invasive breast carcinoma

Abstract Purpose: Pathologists routinely analyze H&amp;E-stained FFPE tissue slides microscopically to arrive at diagnoses for patients. Pathomics, the study of quantitative imaging from such samples, aims to elevate diagnostic accuracy by revealing intricate tissue and cellular details. Our research evaluates how pathomic features from tissue imagery can predict gene expression, as determined by RNA sequencing, offering advancements in the molecular profiling and targeted therapy for invasive breast carcinoma (IBC). Method: We conducted an analysis of 90 regions of interest (ROIs) on FFPE tissue slide images from the TCGA registry for patients with IBC. Using HistomicsTK software, we extracted nearly 300 pathomic features depicting cell morphometry, intensity, and gradient from these regions of interest (ROIs). We then assessed the intra-correlation of the pathomic features within the ROIs of the same tissue slide to identify the most heterogeneous and highly correlating features (n=20) across categories—morphometry, intensity, and gradient—with a Pearsonʼs Correlation coefficient (r) greater than 0.9 and a FDR adjusted p-value less than 0.05. Subsequently, gene expression data in the form of FPKM were obtained for the corresponding tissues from TCGA. We trained a Multitask Elastic Net (MTEN) model on these pathomic features using an 80:20 split for the training and testing sets, with a three-fold cross-validation applied to the training set utilizing ImaGene software. The model's performance was evaluated by measuring the AUC and R² value for the predicted gene expression on the testing set. Result and Biological significance: The testing of the MTEN model using a testing set predicted the expression of three genes identified in the literature as prognostic markers in breast cancer, namely ALDH1L2, MFAP5, and MXRA8, with an AUC greater than 0.8 and an R² above 0.5 at a p-value of less than 0.002. According to the literature, expression of genes from the ALDH1 superfamily in breast cancer correlates with the stage of the disease, triple-negative status, and response to neoadjuvant therapy. The upregulation of MFAP5 in invasive breast carcinomas has been associated with high risk prognostic features, such as higher tumor grade and stage and increased angiogenesis, and poorer outcomes, such as lymph node metastasis. Furthermore, MXRA8 is involved in modulating the progression of human triple-negative breast cancer, likely through its influence on the interactions of tumor cells with their microenvironment. Conclusion: The present study predicts the expression of clinically relevant genes in IBC using a heterogeneous set of pathomic features extracted from FFPE tissue slide imagery. By linking cell and tissue-based morphometric, intensity, and gradient features with gene expression, researchers can gain insights into the molecular mechanisms underlying disease progression. Digital pathology and pathomics may reduce the need for additional genetic testing in critical patient-cases by providing predictive information from routinely acquired pathology slides. Bridging the gap between phenotypic tissue data and molecular data, the predictive capabilities of pathomic features represent a significant advancement in the field of precision medicine. Citation Format: Shrey S. Sukhadia, Digvijay Yadav, Kristen E. Muller. Transformative pathomics in oncology: Harnessing FFPE tissue slide imagery for clinically relevant gene expression prediction in invasive breast carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB392.

Expression and Significance of LINC02418 in Breast Cancer.

The complicated pathogenesis and poor prognosis of breast cancer have become a major difficulty in medical research. This study aims to explore new lncRNA as prognostic markers for breast cancer and explore their roles and molecular mechanisms to lay a foundation for the treatment of cancer patients. The expression of LINC02418 and miR-766-5p in breast cancer tissues and cells was first identified using polymerase chain reaction, and Pearson was used to examine the correlation between the two. The cancer cells activities under different transfection conditions were detected using the Transwell assay and CCK8 assay. The correlation between LINC02418 and patient prognosis was analyzed using multifactor Cox regression and Kaplan-Meier. It was shown that LINC02418 expression was upregulated in breast cancer tissues and cells. There are significant differences in lymph node metastasis and TNM stage between high and low LINC02418 expression groups. The higher the expression of LINC02418, the higher the mortality rate of breast cancer patients. miR-766-5p expression was downregulated and negatively correlated with LINC02418. There are binding sites between LINC02418 and miR-766-5p; Transfection with miR-766-5p inhibitor boosted LINC02418 luciferase activity, but transfection with miR-766-5p mimic decreased it. Knockdown of LINC02418 promoted miR-766-5p expression and inhibited cancer progression, which was alleviated to some extent by transfection with miR-766-5p inhibitors. LINC02418 has the potential to serve as a poor prognostic marker for breast cancer and plays a pro-oncogenic role by targeting miR-766-5p.

Long-Noncoding-RNA HOTAIR Upregulation is Associated with Poor Breast Cancer Outcome: A Systematic Review and Meta Analysis.

Breast cancer is the most frequent cancer among women worldwide with significant disproportionate mortality rates in developing countries. Although clinical management of breast cancer has been immensely improved, refinement in the prognostic and recurrent markers is still needed. Long non-coding RNAs (lncRNA) HOTAIR has recently been associated with poor outcome and is potentially used as a prognostic marker in breast cancer. We comprehensively reviewed studies evaluating lncRNA HOTAIR in association with overall and disease-free survivals in breast cancers. Systematic searches were performed in Pubmed, ProQuest, ScienceDirect, Scopus, Google Scholar, Semantic Scholar, Springer, Nature, Sage Journals, and Wiley databases using combination keywords "long non-coding RNA," "lncRNA," "HOX transcript antisense RNA," "HOTAIR," "breast can-cer," "carcinoma mammae," "prognosis," and "survival." Risk of bias score was used to assess quality of studies, I2 test was conducted to assess heterogeneity. Meta-analysis was performed to compare HOTAIR expression with breast cancer survival rates using STATA v.17 software. Of the total 1,504 screened studies, seven studies were included in the meta-analysis involving 533 patients. High expression of HOTAIR was associated with poor survival rates (pooled HR: 1.69; 95%CI: 1.11-2.59; p=0.015), shorter overall survival (OS) (pooled HR: 1.33; 95%CI: 0.78-2.26; p=0.455), poor disease-free survival (DFS) (pooled HR: 2.40; 95%CI: 1.63-3.53; p<0.001), poor distant metastatic-free survival (MFS) (HR: 1.75; 95%CI: 1.13-2.71; p=0.012). In addition, overexpression of HOTAIR was associated with positive lymph node infiltration (pooled OR: 2.38; 95%CI: 0.53-10.69; p=0.26) and ductal type cancer (pooled OR: 3.27; 95%CI: 1.15-9.30; p=0.03). Upregulation of lncRNA HOTAIR is associated with worse DFS aand MFS that can potentially be used as a prognostic marker in breast cancer patients.

Mitochondrial calcium uniporter as biomarker and therapeutic target for breast cancer: Prognostication, immune microenvironment, epigenetic regulation and precision medicine

IntroductionMitochondrial calcium uniporter (MCU) is a central subunit of MCU complex that regulate the levels of calcium ions within mitochondria. A comprehensive understanding the implications of MCU in clinical prognostication, biological understandings and therapeutic opportunity of breast cancer (BC) is yet to be determined. ObjectivesThis study aims to investigate the role of MCU in predictive performance, tumor progression, epigenetic regulation, shaping of tumor immune microenvironment, and pharmacogenetics and the development of anti-tumor therapy for BC. MethodsThe downloaded TCGA datasets were used to identify predictive ability of MCU expressions via supervised learning principle. Functional enrichment, mutation landscape, immunological profile, drug sensitivity were examined using bioinformatics analysis and confirmed by experiments exploiting human specimens, in vitro and in vivo models. ResultsMCU copy numbers increase with MCU gene expression. MCU expression, but not MCU genetic alterations, had a positive correlation with known BC prognostic markers. Higher MCU levels in BC showed modest efficacy in predicting overall survival. In addition, high MCU expression was associated with known BC prognostic markers and with malignancy. In BC tumor and sgRNA-treated cell lines, enrichment pathways identified the involvement of cell cycle and immunity. miR-29a was recognized as a negative epigenetic regulator of MCU. High MCU levels were associated with increased mutation levels in oncogene TP53 and tumor suppression gene CDH1, as well as with an immunosuppressive microenvironment. Sigle-cell sequencing indicated that MCU mostly mapped on to tumor cell and CD8 T-cells. Inter-databases verification further confirmed the aforementioned observation. miR-29a-mediated knockdown of MCU resulted in tumor suppression and mitochondrial dysfunction, as well as diminished metastasis. Furthermore, MCU present pharmacogenetic significance in cellular docetaxel sensitivity and in prediction of patients’ response to chemotherapeutic regimen. ConclusionMCU shows significant implication in prognosis, outcome prediction, microenvironmental shaping and precision medicine for BC. miR-29a-mediated MCU inhibition exerts therapeutic effect in tumor growth and metastasis.

Abstract 3486: Triple hormone receptor signatures as novel prognostic markers in breast cancer

Abstract Background: Tumor phenotype across various cancers, including breast cancer, is predominantly shaped by a synergy between genomic alterations and the cell-of-origin from which the tumor originates. These elements collectively influence crucial aspects like tumor aggressiveness, treatment response, and patient prognosis. While existing research highlights that the role of cell-of-origin in shaping the molecular architecture of breast cancer, leveraging this information for actionable clinical insights has proven challenging. Here, we introduce two robust models leveraging cellular ancestry signatures of breast luminal cells to improve patient stratification and outcome prediction. Methods: In this study, we developed a unique gene signature anchored in the expression levels of triple hormone receptors (THR)—namely androgen (AR), estrogen (ER), and vitamin D (VDR)—in breast cancer cells. Building on this, we formulated two distinct mRNA markers, THR-50 and THR-70, aimed at categorizing breast tumors based on their THR expression profiles. These markers were rigorously validated across 65 independent breast cancer studies, involving a total of 6,679 patients, utilizing Kaplan-Meier survival curves, Cox proportional hazards models, and unsupervised clustering analyses. Results: Our findings indicate that both THR-50 and THR-70 are robustly associated with overall survival and recurrence-free survival in breast cancer patients across all datasets evaluated. Importantly, these THR signatures demonstrate broad applicability across various breast cancer subtypes, grades, and treatment phases—unlike existing prognostic markers that tend to be subtype-specific. Additionally, the THR signatures have revealed four unique patient clusters with divergent survival outcomes, three of which are ER-positive and one is ER-negative. Additionally, we developed an immune-based signature (i20) which can further categorize patients within the ER-negative cluster into two subgroups: one with a highly favorable prognosis, comparable to the ER-positive subtypes, and another that is characterized by exceedingly poor survival outcomes. Conclusion: The THR-based cellular ancestry signatures open a new avenue in understanding the intricacies of breast cancer biology. These signatures offer a robust and stable framework for developing other prognostic markers, thus providing an enhanced stratification of existing breast cancer categories as well as creating new classifications with more distinct survival estimates. Citation Format: Mohamed Omar, J. Chuck Harrell, Rulla M. Tamimi, Luigi Marchionni, Tan Ince. Triple hormone receptor signatures as novel prognostic markers in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3486.

Multi-omics analysis reveals the unique landscape of DLD in the breast cancer tumor microenvironment and its implications for immune-related prognosis

BackgroundCuproptosis, i.e., copper-induced programmed cell death, has potential implications in cancer therapy. However, the impact of the cuproptosis-related gene (CRG) dihydrolipoyl dehydrogenase (DLD) on breast cancer (BC) prognosis remains underexplored. MethodsWe employed real-time quantitative PCR and multiplexed immunostaining techniques to quantify DLD expression in both BC and the adjacent non-cancerous tissues. Immunofluorescence analysis was employed to assess the influence of DLD on immune cells and immunological checkpoints in the BC microenvironment. DLD knockdown experiments were conducted in BC cell lines MDA-MB-468 and SK-BR-3, with knockdown efficiency validated via western blot. Subsequently, we performed the cell counting kit-8 (CCK-8) assay, clone formation assay, Transwell migration assay, and invasion assay. To construct a prognostic model, we employed a Lasso-Cox regression analysis of immune-related genes associated with DLD. Additionally, we established a competing endogenous RNA network based on CRGs to evaluate potential regulatory pathways. ResultsCompared to the adjacent tissues, BC tissues exhibited markedly elevated DLD expression levels. In vitro experiments demonstrated that DLD knockdown effectively inhibited BC cell migration, invasion, and proliferation. DLD exhibited positive correlations with CD68+ macrophages and PD-L1 in the tumor, as well as with macrophages and CD4+ T cells in the stroma. Tumor regions with high DLD expression were enriched in PD-L1 and macrophages, while stromal regions with high DLD expression contained CD4+ T cells and macrophages. The AUC values for 1-, 3-, and 5-year overall survival in TCGA-BRCA training set were 0.67, 0.66, and 0.66, respectively. A nomogram with a C-index of 0.715 indicated that risk score, tumor stage, and age could serve as independent prognostic factors for BC. ConclusionOur findings underscore the significant predictive significance of DLD in BC and its influence on the tumor microenvironment. DLD represents a promising diagnostic and prognostic marker for BC, offering novel avenues for the identification of therapeutic targets and the enhancement of immunotherapy in BC.

The Correlation between Morpho-Dynamic Contrast-Enhanced Mammography (CEM) Features and Prognostic Factors in Breast Cancer: A Single-Center Retrospective Analysis.

Breast cancer, a major contributor to female mortality globally, presents challenges in detection, prompting exploration beyond digital mammography. Contrast-Enhanced Mammography (CEM), integrating morphological and functional information, emerges as a promising alternative, offering advantages in cost-effectiveness and reduced anxiety compared to MRI. This study investigates CEM's correlation with breast cancer prognostic factors, encompassing histology, grade, and molecular markers. In a retrospective analysis involving 114 women, CEM revealed diverse lesion characteristics. Statistical analyses identified correlations between specific CEM features, such as spiculated margins and irregular shape, and prognostic factors like tumor grade and molecular markers. Notably, spiculated margins predicted lower grade and HER2 status, while irregular shape correlated with PgR and Ki-67 status. The study emphasizes CEM's potential in predicting breast cancer prognosis, shedding light on tumor behavior. Despite the limitations, including sample size and single-observer analysis, the findings advocate for CEM's role in stratifying breast cancers based on biological characteristics. CEM features, particularly spiculated margins, irregular shape, and enhancement dynamics, may serve as valuable indicators for personalized treatment decisions. Further research is crucial to validate these correlations and enhance CEM's clinical utility in breast cancer assessment.