Predictive Biomarker In Breast Cancer Research Articles

Plasma Circular RNAs as Biomarkers for Breast Cancer.

Breast cancer (BC) is currently the most common neoplasm, the second leading cause of cancer death in women worldwide, and is a major health problem. The discovery of new biomarkers is crucial to improve our knowledge of breast cancer and strengthen our clinical approaches to diagnosis, prognosis, and follow-up. In recent decades, there has been increasing interest in circulating RNA (circRNA) as modulators of gene expression involved in tumor development and progression. The study of circulating circRNAs (ccircRNAs) in plasma may provide new non-invasive diagnostic, prognostic, and predictive biomarkers for BC. This review describes the latest findings on BC-associated ccircRNAs in plasma and their clinical utility. Several ccircRNAs in plasma have shown great potential as BC biomarkers, especially from a diagnostic point of view. Mechanistically, most of the reported BC-associated ccircRNAs are involved in the regulation of cell survival, proliferation, and invasion, mainly via MAPK/AKT signaling pathways. However, the study of circRNAs is a relatively new area of research, and a larger number of studies will be crucial to confirm their potential as plasma biomarkers and to understand their involvement in BC.

Emerging measurements for tumor-infiltrating lymphocytes in breast cancer.

Tumor-infiltrating lymphocytes are a general term for lymphocytes or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating lymphocytes to be robust prognostic and predictive biomarkers in breast cancer. Recently, immune checkpoint inhibitors, which directly target tumor-infiltrating lymphocytes, have become part of standard of care treatment for triple-negative breast cancer. Surprisingly, tumor-infiltrating lymphocytes quantified by conventional methods do not predict response to immune checkpoint inhibitors, which highlights the heterogeneity of tumor-infiltrating lymphocytes and the complexity of the immune network in the tumor microenvironment. Tumor-infiltrating lymphocytes are composed of diverse immune cell populations, including cytotoxic CD8-positive T lymphocytes, B cells and myeloid cells. Traditionally, tumor-infiltrating lymphocytes in tumor stroma have been evaluated by histology. However, the standardization of this approach is limited, necessitating the use of various novel technologies to elucidate the heterogeneity in the tumor microenvironment. This review outlines the evaluation methods for tumor-infiltrating lymphocytes from conventional pathological approaches that evaluate intratumoral and stromal tumor-infiltrating lymphocytes such as immunohistochemistry, to the more recent advancements in computer tissue imaging using artificial intelligence, flow cytometry sorting and multi-omics analyses using high-throughput assays to estimate tumor-infiltrating lymphocytes from bulk tumor using immune signatures or deconvolution tools. We also discuss higher resolution technologies that enable the analysis of tumor-infiltrating lymphocytes heterogeneity such as single-cell analysis and spatial transcriptomics. As we approach the era of personalized medicine, it is important for clinicians to understand these technologies.

Searching for the "Holy Grail" of breast cancer recurrence risk: a narrative review of the hunt for a better biomarker and the promise of circulating tumor DNA (ctDNA).

This paper is a narrative review of a major clinical challenge at the heart of breast cancer care: determining which patients are at risk of recurrence, which require systemic therapy, and which remain at risk in the survivorship phase of care despite initial therapy. We review the literature on prognostic and predictive biomarkers in breast cancer with a focus on detection of minimal residual disease. While we have many tools to estimate and refine risk that are used to individualize local and systemic therapy, we know that we continue to over treat many patients and undertreat others. Many patients also experience what is, at least in hindsight, needless fear of recurrence. In this review, we frame this dilemma for the practicing breast oncologist and discuss the search for what we term the "holy grail" of breast cancer evaluation: the ideal biomarker of residual distant disease. We review the history of attempts to address this problem and the up-to-date science on biomarkers, circulating tumor cells and circulating tumor DNA (ctDNA). This review suggests that the emerging promise of ctDNA may help resolve a crticical dilemma at the heart of breast cancer care, and improve prognostication, treatment selection, and outcomes for patients with breast cancer.

Tumor infiltrating lymphocytes (TILs) in triple negative breast cancer

Tumor infiltrating lymphocytes (TILs) are a promising inexpensive prognostic and predictive biomarker in breast cancer. High levels of TILs are associated with improved survival and higher probability to achieve pathological complete response in triple-negative breast cancer (TNBC). To assess the level of TILs in TNBC samples and analyze the association between the level of TILs and the main pathological parameters, to identify their impact on long-term results. The study included information on 140 patients with I-III stage TNBC and estrogen receptors <10%. Tumor tissue samples at baseline biopsies were evaluated the histological type, HER2 expression, estrogen expression levels, Ki-67 and TILs. The pathological response was evaluated according to the ypTNM, Miller-Payne, and RCB classifications. The average level of TILs in biopsy specimens before NACT was 29.3±23.1%. Low levels of TILs (<10%) were defined in 21% of cases, intermediate levels (≥10% to ≤40%) in 55% of cases, and high levels (>40%) in 24% of cases. Using the two-tiered system, low TILs (≤40%) were defined in 76% and high TILs (>40%) in 24% of cases. The level of TILs was correlated with histological grade (R=0.187; p=0.027) and estrogen receptor expression level (R=0.211; p=0.012). There were no significant differences depending on the level of TILs and other pathological parameters. Three-year event-free survival (EFS) in patients with high TILs levels was 95% versus 65% in the low TILs group (p=0.037). Stromal TILs are an important prognostic biomarker in TNBC. Using a cutoff of 40%, high TILs are significantly associated with longer EFS.

Targeting the Tumor Microenvironment in Breast Cancer: Prognostic and Predictive Significance and Therapeutic Opportunities

Breast cancer is one of the most prevalent tumors among women. Its prognosis and treatment outcomes depend on factors related to tumor cell biology. However, recent studies have revealed the critical role of the tumor microenvironment (TME) in the development, progression, and treatment response of breast cancer. In this review, we explore the different components of the TME and their relevance as prognostic and predictive biomarkers in breast cancer. In addition, techniques for assessing the tumor microenvironment, such as immunohistochemistry or gene expression profiling, and their clinical utility in therapeutic decision-making are examined. Finally, therapeutic strategies targeting the TME are reviewed, highlighting their potential clinical benefits. Overall, this review emphasizes the importance of the TME in breast cancer and its potential as a clinical tool for better patient stratification and the design of personalized therapies.

The Value of Tumor Infiltrating Lymphocytes (TIL) for Predicting the Response to Neoadjuvant Chemotherapy (NAC) in Breast Cancer according to the Molecular Subtypes.

The antitumor host immune response is an important factor in breast cancer, but its role is not fully established. The role of tumor infiltrating lymphocytes (TIL) as an immunological biomarker in breast cancer has been significantly explored in recent years. The number of patients treated with neoadjuvant chemotherapy (NAC) has increased and the identification of a biomarker to predict the probability of pCR (pathological complete response) is a high priority. We evaluated 334 cases of BC treated with NAC followed by surgical resection from 2020-2022 at the Ist Clinic of Oncological Surgery, Oncological Institute "Prof Dr I Chiricuta" Cluj Napoca. Of the above, 122 cases were available for histological evaluation both in pre-NAC biopsy and post-NAC resection tissue. Evaluation of biopsy fragments and resection parts were performed using hematoxylin eosin (H&E). The TIL evaluation took place according to the recommendations of the International TIL Working Group (ITILWG). There was a strong association between elevated levels of pre-NAC TIL. At the same time, there is a statistically significant correlation between stromal TIL and tumor grade, the number of lymph node metastases, the molecular subtype and the number of mitoses (p < 0.005). Intratumoral TIL showed a significant correlation with tumor size, distant metastasis, molecular subtype, number of mitosis, stage and lymph node metastasis (p < 0.005). We also demonstrated that high pre-NAC STIL represents a strong predictive marker for pCR. This study reveals the role of TIL as a predictive biomarker in breast cancer not only for the well-established TNBC (triple negative breast cancer) and HER2+ (Her2 overexpressed) subtypes but also in Luminal A and B molecular subtypes. In this scenario, the evaluation of sTIL as a novel predictive and therapy-predicting factor should become a routinely performed analysis that could guide clinicians when choosing the most appropriate therapy.

MAF1 is a predictive biomarker in HER2 positive breast cancer.

RNA polymerase III transcription is pivotal in regulating cellular growth and frequently deregulated in various cancers. MAF1 negatively regulates RNA polymerase III transcription. Currently, it is unclear if MAF1 is universally deregulated in human cancers. Recently, MAF1 expression has been demonstrated to be altered in colorectal and liver carcinomas and Luminal B breast cancers. In this study, we analyzed clinical breast cancer datasets to determine if MAF1 alterations correlate with clinical outcomes in HER2-positive breast cancer. Using various bioinformatics tools, we screened breast cancer datasets for alterations in MAF1 expression. We report that MAF1 is amplified in 39% of all breast cancer sub-types, and the observed amplification co-occurs with MYC. MAF1 amplification correlated with increased methylation of the MAF1 promoter and MAF1 protein expression is significantly decreased in luminal, HER2-positive, and TNBC breast cancer subtypes. MAF1 protein expression is also significantly reduced in stage 2 and 3 breast cancer compared to normal and significantly decreased in all breast cancer patients, regardless of race and age. In SKBR3 and BT474 breast cancer cell lines treated with anti-HER2 therapies, MAF1 mRNA expression is significantly increased. In HER2-positive breast cancer patients, MAF1 expression significantly increases and correlates with five years of relapse-free survival in response to trastuzumab treatment, suggesting MAF1 is a predictive biomarker in breast cancer. These data suggest a role for MAF1 alterations in HER2-positive breast cancer. More extensive studies are warranted to determine if MAF1 serves as a predictive and prognostic biomarker in breast cancer.

SIK2-positive tumor epithelial cells in breast cancer maybe potential anti-cancer messengers: A systematic analysis from a single-cell perspective.

Breast cancer is the most common malignancy in the world and one of the leading causes of cancer death, which is a heterogeneous disease involving genetic and environmental factors. Breast cancer stem cells (BCSCs) are the main players in the aggressiveness of different tumors, at the same time, these cells are the main challenge for cancer treatment. There are multiple treatment options for breast cancer (BC) patients and the lack of understanding of prognostic and predictive biomarkers for breast cancer is a potential research direction for us to develop better treatments in the future. In this paper, we conducted a correlation analysis between SIK2 and clinical traits by searching numerous BRCA datasets in the GEO database. The model was constructed and validated by incorporating tumor samples from the TCGA-BRCA cohort. Surprisingly, we found differential expression of SIK2 gene in individual tumor samples from the UCSC database. Subsequently, we found significantly high expression of SIK2 in epithelial cells by comparing the differential expression of SIK2 in different cell subpopulations and performed subsequent immune infiltration and pathway correlation analysis. Differential genes in SIK2+ epithelial cells, which may be potential therapeutic targets for breast cancer. In conclusion, our results suggest that SIK2 may be a potential prognostic and predictive biomarker that could serve as an oncogenic messenger for breast cancer. This discovery of SIK2 may provide more valuable references for potential therapeutic tools for breast cancer.

Standardized pathology report for HER2 testing in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

Since the release of the DESTINY-Breast04 (DB-04) trial findings in June 2022, the field of pathology has seen a renaissance of HER2 as a predictive biomarker in breast cancer. The trial focused on patients with metastatic breast cancer who were classified as "HER2-low," i.e., those with immunohistochemistry (IHC) HER2 1 + or 2 + and negative in situ hybridization (ISH) results. The study revealed that treating these patients with trastuzumab deruxtecan (T-DXd) instead of the oncologist's chosen chemotherapy led to outstanding improvements in survival. This has challenged the existing binary HER2 pathological classification system, which categorized tumors as either positive (overexpression/amplification) or negative, as per the ASCO/CAP 2018 guideline reaffirmed by ASCO/CAP 2023 guideline update. Given that DB-04 excluded patients with HER2 IHC score 0 status, the results of the ongoing DB-06 trial may shed further light on the potential benefits of T-DXd therapy for these patients. Roughly half of all breast cancers are estimated to belong to the HER2-low category, which does not represent a distinct or specific subtype of cancer. Instead, it encompasses a diverse group of tumors that exhibit clinical, morphological, immunohistochemical, and molecular variations. However, HER2-low offers a distinctive biomarker status that identifies a specific therapeutic regimen (i.e.,T-DXd) linked to a favorable prognosis in breast cancer. This unique association emphasizes the importance of accurately identifying these tumors. Differentiating between a HER2 IHC score 0 and score 1 + has not been clinically significant until now. To ensure accurate classification and avoid misdiagnosis, it is necessary to adopt standardized procedures, guidelines, and specialized training for pathologists in interpreting HER2 expression in the lower spectrum. Additionally, the utilization of artificial intelligence holds promise in supporting this endeavor. Here, we address the current state of the art and unresolved issues in assessing HER2-low status, with a particular emphasis on the score 0. We explore the dilemma surrounding the exclusion of HER2-zero patients from potentially beneficial therapy based on traditional HER2 testing. Additionally, we examine the clinical context, considering that DB-04 primarily involved heavily pretreated late-stage metastatic breast cancers. We also delve into emerging evidence suggesting that extrapolating HER2-low status from the original diagnosis may lead to misleading results. Finally, we provide recommendations for conducting high-quality testing and propose a standardized pathology report in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.

Tumor-infiltrating lymphocytes (TILs) for prediction of response to platinum-based neoadjuvant chemotherapy (NACT) in triple-negative breast cancer (TNBC).

e12620 Background: According to several previous trials the rate of pathological complete response (pCR) for patients with TNBC is increased when carboplatin is added to NACT. However, it is largely unknown which group of patients would truly benefit from platinum-based NACT and for whom chemotherapy could be de-escalated. Several clinical trials have evaluated the stromal TILs as an important prognostic and predictive biomarker in breast cancer. We assessed the pCR rates and the outcomes in patients with TNBC randomized to receive NACT ± Carboplatin regarding TILs status. Methods: The clinical data were obtained from 132 patients diagnosed with TNBC (ER&amp;PgR &lt; 10%) and treated with either anthracycline-taxane NACT (n = 68) or сarboplatin-based chemotherapy (n = 64) from 2017 to 2022 at N.N. Petrov National Medicine Research Center of Oncology. TILs were evaluated in 132 formalin-fixed paraffin-embedded tumor tissue samples stained with H&amp;E at baseline biopsies according to guidelines from the International TILs Working Group. Classification of TILs into low ( &lt; 10%), intermediate (≤10% to &lt; 40%) and high (≥ 40%) levels was performed. Data are presented using the methods of descriptive statistics. The differences between groups were assessed using the Сhi-square test. P-values below 0.05 were considered statistically significant. Results: The proportion of patients who achieved a pCR was higher in the carboplatin group 66% than in patients without carboplatin 35% (OR 3,5; 95% CI 1,71-7,17; p = 0,0006). There were 25 (18.9%), 77 (58.3%) and 30 (22.7%) patients with low ( &lt; 10%), intermediate (≤10% to &lt; 40%) and high (≥ 40%) levels of TILs, respectively. In total, the tumors with high TILs had a pCR rate of 63.3%, compared with 46.1% for low TILs (OR 2,0; 95% CI 0,87-4,67; p = 0,097). No significant statistical difference in pCR rates was shown between carboplatin-based and standard NACT groups with high TILs - 71% and 54%, respectively (OR 2,06; 95% CI 0,45-9,30; p = 0,346). When analyzing a group with low TILs infiltration, the pCR was more frequent in the platinum-based 64% compared to 31% in the standard NACT group (OR 3,9; 95% CI 1,72-9,00; p = 0,0011). Conclusions: These data may support the de-escalation of carboplatin-based NACT in patients diagnosed with TNBC with high TILs infiltration. Further investigations are warranted to explore the predictive value of TILs in platinum-based NACT. [Table: see text]

Evaluation of triple negative breast cancer with heterogeneous immune infiltration.

Tumor infiltrating lymphocytes (TILs) are known to be a prognostic and predictive biomarker in breast cancer, particularly in triple negative breast cancer (TNBC) patients. International guidelines have been proposed to evaluate them in the clinical setting as a continuous variable, without a clear defined cut-off. However, there are scenarios where the immune infiltration is heterogeneous that some areas of the patient's tumour have high numbers of TILs while other areas completely lack them. This spontaneous presentation of a heterogeneous immune infiltration could be a great opportunity to study why some tumours present TILs at diagnosis but others do not, while eliminating inter patient's differences. In this study, we haveidentifiedfive TNBC patients that showed great TIL heterogeneity, with areas of low (≤5%) and high (≥50%) numbers of TILs in their surgical specimens. To evaluate immune infiltration heterogeneity, we performed and analyzed bulk RNA-sequencing in three independent triplicates from the high and low TIL areas of each patient. Gene expression was homogeneous within the triplicates in each area but was remarkable different between TILs regions. These differences were not only due to the presence of TILs as there were other non-inflammatory genes and pathways differentially expressed between the two areas. This highlights the importance of intratumour heterogeneity driving the immune infiltration, and not patient's characteristics like the HLA phenotype, germline DNA or immune repertoire.

RMI2 is a novel prognostic and predictive biomarker for breast cancer.

RecQ-mediated genome instability 2 (RMI2) maintains genome stability by promoting DNA damage repair. It has been reported to accelerate the progression of several tumors. However, the functional mechanism of RMI2 in breast cancer remains unclear. Gene expression profiles were obtained from TCGA, GTEx, and GEO databases. The expression of RMI2 and its prognostic value in breast cancer was explored. In addition, we calculated pooled standardized mean deviation (SMD) and performed a summary receiver operating characteristic (sROC) curve analysis to further determine RMI2 expression status and diagnostic significance. The functions and related signaling pathways were investigated based on GO and KEGG analyses. The PPI network was constructed by combining the STRING database and Cytoscape software. Subsequently, in vitro assays were conducted to detect the effect of RMI2 on the proliferation and migration of breast cancer cells. The expression of RMI2 was markedly upregulated in breast cancer tissues relative to that in normal tissues. Moreover, pooled SMD further confirmed the overexpression of RMI2 in breast cancer (SMD=1.29, 95% confidence interval (CI): 1.18-1.41, p=0.000). The sROC curve analysis result suggested that RMI2 had a relatively high diagnostic ability in breast cancer (AUC=0.87, 95% CI: 0.84-0.90). High RMI2 expression was associated with poor prognosis. GO and KEGG analyses revealed that RMI2 was closely related to cell adhesion, various enzyme activities, and PI3K/AKT signaling pathway. PPI analysis showed that RMI2 had interactions with proteins involved in DNA damage repair. knockdown of RMI2 remarkably inhibited the proliferation and migration of breast cancer cells, while overexpression of RMI2 exerted the opposite effects. Furthermore, we identified that RMI2 accelerates the proliferation and migration of breast cancer cells via activation of the PI3K/AKT pathway. The results suggest that RMI2 is a potential diagnostic and prognostic biomarker associated with cell proliferation and migration, and may be used as a novel therapeutic target for breast cancer in the future.

Genomic alteration profile and PD-L1 expression among different breast cancer subtypes in Chinese population and their correlations.

There were limitations existing in programmed cell-death ligand 1 (PD-L1) as predictive biomarkers for breast cancer (BC), hence exploring the correlation between PD-L1 levels and other biomarkers in BC may become a very useful therapeutic clinical tool. A total of 301 Chinese patients with different BC subtypes including 47 HR+/HER2+, 185 HR+/HER2-, 38 HR-/HER2+, and 31 triple-negative breast cancer (TNBC) were enrolled in our study. Next-generation sequencing based Yuansu450 gene panel was used for genomic alteration identification and PD-L1 expression was tested using immunohistochemistry. The most prevalent BC-related mutations were TP53 mutations, followed by mutations in PIK3CA, ERBB2, CDK12, and GATA3 in our Chinese cohort. We found that mutations DDR2 and MYCL were only mutated in HR-/HER2+ subtype, whereas H3-3A and NRAS mutations were only occurred in HR-/HER2- subtype. The percentage of patients with PD-L1-positive expression was higher in patients with HR-/HER2- mainly due to the percentage of PD-L1-high level. Mutational frequencies of TP53, MYC, FAT4, PBRM1, PREX2 were observed to have significant differences among patients with different BC subtypes based on PD-L1 levels. Moreover, a positive correlation was observed between TMB and PD-L1 level in HR+/HER2- subtype, and showed that the proportion of patients with high PD-L1 expression was higher than that of patients with low PD-L1 expression in the HR+/HER2- and HR+/HER2+ cohorts with high Ki67 expression. The genomic alterations based on PD-L1 and other biomarkers of different cohorts may provide more possibilities for the treatment of BC with different subtypes.

Update on prognostic and predictive biomarkers of breast cancer.

Breast cancer represents a heterogeneous group of human cancer at both histological and molecular levels. Estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) are the most commonly used biomarkers in clinical practice for making treatment plans for breast cancer patients by oncologists. Recently, PD-L1 testing plays an important role for immunotherapy for triple-negative breast cancer. With the increased understanding of the molecular characterization of breast cancer and the emergence of novel targeted therapies, more potential biomarkers are needed for the development of more personalized treatments. In this review, we summarized several main prognostic and predictive biomarkers in breast cancer at genomic, transcriptomic and proteomic levels, including hormone receptors, HER2, Ki67, multiple gene expression assays, PD-L1 testing, mismatch repair deficiency/microsatellite instability, tumor mutational burden, PIK3CA, ESR1 andNTRK and briefly introduced the roles of digital imaging analysis in breast biomarker evaluation.

Predictive biomarkers for molecularly targeted therapies and immunotherapies in breast cancer.

Globally, breast cancer is the most common malignancy in women. Substantial efforts have been made to develop novel therapies, including targeted therapies and immunotherapies, for patients with breast cancer who do not respond to standard therapies. Consequently, new targeted therapies, such as cyclin-dependent kinase 4 and 6 inhibitors, poly (ADP-ribose) polymerase inhibitors, phosphoinositide 3-kinase inhibitor, and antibody-drug conjugates targeting human epidermal growth factor receptor 2 or trophoblast cell surface antigen-2, and immune checkpoint inhibitor targeting programmed cell death-1, have been developed and are now in clinical use. However, only some patients have benefited from these novel therapies; therefore, the identification and validation of reliable or more accurate biomarkers for predicting responses to these agents remain a major challenge. This review summarizes the currently available predictive biomarkers for breast cancer and describes recent efforts undertaken to identify potential predictive markers for molecularly targeted therapies and immune checkpoint inhibitors.

Anthracycline-Free Neoadjuvant Treatment in Patients with HER2-Positive Breast Cancer: Real-Life Use of Pertuzumab, Trastuzumab and Taxanes Association with an Exploratory Analysis of PIK3CA Mutational Status.

Simple SummaryThis retrospective observational study aims at highlighting the response to pertuzumab, trastuzumab and docetaxel treatment (THP), without using anthracycline, in patients with HER2-positive early breast cancer. We add evidence to the suitability of THP in real life to reach higher pathological complete response rates, with a good safety profile for patients. An exploratory analysis of the mutational status of PIK3CA was performed as well, and 21% mutated samples were identified, with overall higher pCR rates in PIK3CA mutant patients and, particularly, in those who were THP-treated. Our original results open the door to further studies focused on more in-depth analysis of the molecular and clinical features related to the response to anthracycline-free neoadjuvant treatment in HER2-positive early breast cancer patients.HER2 is considered one of the most traditional prognostic and predictive biomarkers in breast cancer. Literature data confirmed that the addition of pertuzumab to a standard neoadjuvant chemotherapy backbone (either with or without anthracyclines), in patients with human epidermal growth factor receptor 2 (HER2)-positive early breast cancer (EBC), leads to a higher pathological complete response (pCR) rate, which is known to correlate with a better prognosis. In this retrospective analysis, 47 consecutive patients with HER2-positive EBC received sequential anthracyclines and taxanes plus trastuzumab (ATH) or pertuzumab, trastuzumab and docetaxel (THP). Despite the limited sample size, this monocentric experience highlights the efficacy (in terms of pCR) and safety of THP in the neoadjuvant setting of HER2-positive EBC as an anthracycline-free approach. Given the role of PIK3CA as a prognostic and therapeutic target in breast cancer, tumors were also analyzed to assess the PIK3CA mutational status. Thirty-eight out of forty-seven patients were evaluated, and PIK3CA variants were identified in 21% of tumor samples: overall, one mutation was detected in exon 4 (2.6%), two in exon 9 (5.3%) and four in exon 20 (10.5%). Of note, one sample showed concurrent mutations in exons 9 (codon 545) and 20 (codon 1047). Among patients reaching pCR (n = 13), 38.5% were PIK3CA mutants; on the other hand, among those lacking pCR (n = 25), just 12% showed PIK3CA variants. Regarding THP-treated mutant patients (n = 5), 80% reached pCR (three hormone-receptor-negative, one hormone-receptor-positive). Interestingly, the only patient not achieving pCR had a tumor with two co-occurring PIK3CA mutations. In conclusion, this study provides new evidence about the efficacy and good safety profile of THP, compared to the ATH regimen, as an anthracycline-free neoadjuvant treatment of HER2-positive EBC. Further studies on larger/multicentric cohorts are planned for more in-depth analysis to confirm our molecular and clinical results.

Prognostic and Predictive Value of CCND1/Cyclin D1 Amplification in Breast Cancer With a Focus on Postmenopausal Patients: A Systematic Review and Meta-Analysis.

BackgroundUp to 80% of breast cancers (BCa) are estrogen receptor positive and current treatments target the estrogen receptor (endocrine therapies) and/or CDK4/6 (CDK4/6 inhibitors). CCND1 encodes the protein cyclin D1, responsible for regulation of G1 to S phase transition in the cell cycle. CCND1 amplification is common in BCa and contributes to increased cyclin D1 expression. As there are signalling interactions between cyclin D1 and the estrogen receptor, understanding the impact of CCND1 amplification on estrogen receptor positive patients’ disease outcomes, is vital. This review aims to evaluate CCND1 amplification as a prognostic and predictive biomarker in BCa.Materials and MethodsPublications were retrieved from the databases: PubMed, MEDLINE, Embase and Cochrane library. Exclusion criteria were duplication, publication type, non-English language, in vitro and animal studies, not BCa, male BCa, premenopausal BCa, cohort size <35, CCND1 amplification not reported. Publications with cohort duplication, and inadequate recurrence free survival (RFS) and overall survival (OS) data, were also excluded. Included publications were assessed for Risk of Bias (RoB) using the Quality In Prognosis Studies tool. Statistical analyses (Inverse Variance and Mantel-Haenszel) were performed in Review Manager. The PROSPERO registration number is [CRD42020208179].Results CCND1 amplification was significantly associated with positive estrogen receptor status (OR:1.70, 95% CI:1.19-2.43, p = 0.004) and cyclin D1 overexpression (OR: 5.64, 95% CI: 2.32-13.74, p=0.0001). CCND1 amplification was significantly associated with shorter RFS (OR: 1.64, 95% CI: 1.13-2.38, p = 0.009), and OS (OR: 1.51, 95% CI: 1.19-1.92, p = 0.0008) after removal of studies with a high RoB. In endocrine therapy treated patients specifically, CCND1 amplification predicted shorter RFS (HR: 2.59, 95% CI: 1.96-3.41, p < 0.00001) and OS (HR: 1.59, 95% CI: 1.00-2.49, p = 0.05) also after removal of studies with a high RoB.ConclusionWhile a lack of standardised approach for the detection of CCND1 amplification is to be considered as a limitation, CCND1 amplification was found to be prognostic of shorter RFS and OS in BCa. CCND1 amplification is also predictive of reduced RFS and OS in endocrine therapy treated patients specifically. With standardised methods and cut offs for the detection of CCND1 amplification, CCND1 amplification would have potential as a predictive biomarker in breast cancer patients.Systematic Review Registration https://www.crd.york.ac.uk/prospero/, identifier CRD42020208179.

Artificial intelligence (AI)–powered spatial analysis of tumor-infiltrating lymphocytes (TIL) for prediction of response to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC).

595 Background: Stromal TIL are a well-recognized prognostic and predictive biomarker in breast cancer. There is a need for tools assisting visual assessment of TIL, to improve reproducibility as well as for convenience. This study aims to assess the clinical significance of AI-powered spatial TIL analysis in the prediction of pathologic complete response (pCR) after NAC in TNBC patients. Methods: H&amp;E stained slides and clinical outcomes data were obtained from stage I – III TNBC patients treated with NAC in two centers in Korea. For spatial TIL analysis, we used Lunit SCOPE IO, an AI-powered H&amp;E Whole-Slide Image (WSI) analyzer, which identifies and quantifies TIL within the cancer or stroma area. Lunit SCOPE IO was developed with a 13.5 x 109 micrometer2 area and 6.2 x 106 TIL from 17,849 H&amp;E WSI of multiple cancer types, annotated by 104 board-certified pathologists. iTIL score and sTIL score were defined as area occupied by TIL in the intratumoral area (%) and the surrounding stroma (%), respectively. Immune phenotype (IP) of each slide was defined from spatial TIL calculation, as inflamed (high TIL density in tumor area), immune-excluded (high TIL density in stroma), or desert (low TIL density overall). Results: A total of 954 TNBC patients treated from 2006 to 2019 were included in this analysis. pCR (ypT0N0) was confirmed in 261 (27.4%) patients. The neoadjuvant regimens used were mostly anthracycline (97.8%) and taxane (75.1%) -based, with 116 (12.1%) patients receiving additional platinum and 41 (4.3%) patients treated as part of immune checkpoint inhibitor or PARP inhibitor clinical trials. The median iTIL score and sTIL score were 4.3% (IQR 3.2 – 5.8) and 8.1% (IQR 6.3 – 13.4), respectively. The mean iTIL score was significantly higher in patients who achieved pCR after NAC (5.8% vs. 4.5%, p &lt; 0.001), and a similar difference was observed with sTIL score (12.1%.1 vs. 9.4%, p &lt; 0.001). iTIL score was found to remain as an independent predictor of pCR along with cT stage and Ki-67 in the multivariable analysis (adjusted odds ratio 1.211 (95% CI 1.125 – 1.304) per 1 point (%) change in the score, p &lt;0.001). By IP groups, 291 (30.5%) patients were classified as inflamed, 502 (52.6%) as excluded, and 161 (16.9%) as desert phenotype. The patients with inflamed phenotype were more likely to achieve pCR (44.7%) than other phenotypes (19.8%, p &lt; 0.001). Conclusions: AI-powered spatial TIL analysis could assess TIL densities in the cancer area and surrounding stroma of TNBC, and TIL density scores and IP classification could predict pCR after NAC.

Insitu hybridization for the assessment of urokinase plasminogen activator and plasminogen activator inhibitor type‑1 informalin‑fixed paraffin‑embedded breast cancer specimens.

Urokinase plasminogen activator (uPA) and its inhibitor, plasminogen activator inhibitor type1 (PAI‑1), have been reported as prognostic and predictive biomarkers in breast cancer, particularly in patients with node‑negative tumors. uPA and PAI‑1 expression levels classify patients into a poor‑prognosis subgroup, requiring adjuvant chemotherapy and a favorable‑prognosis subgroup, which can be considered for de‑escalation. However, the clinical use of these two biomarkers remains limited, since fresh‑frozen/fresh tumor samples are currently required for their quantification. The aim of the present study was to compare PLAU and SERPINE1 mRNA expression levels (corresponding to uPA and PAI‑1 proteins, respectively), assessed using insitu hybridization in 83 formalin‑fixed paraffin‑embedded (FFPE) breast tumor samples, with uPA and PAI‑1 protein expression assessed using immunometric assay with paired fresh‑frozen breast cancer samples. The results from the two methods significantly correlated as regards uPA quantification; however, >30% of the samples were discordant, according to the clinically validated threshold. Concordance between the two analytical methods was less prominent for PAI‑1 protein and SERPINE1 mRNA. Taken together, the results of the present study indicate that although PLAU and SERPINE1 mRNA may be reliably detected in FFPE samples using insitu hybridization, this technology cannot be used as a substitute for the replacement of the immunometric assay‑derived quantification on fresh‑frozen samples.

The concordance between IHC and ISH for HER-2 testing in breast cancer in Nakhon Pathom Hospital, Thailand, based on the ASCO/CAP 2018 guidelines: a retrospective study.

Human epidermal growth factor receptor 2 (HER-2) is the prognostic and predictive biomarker for breast cancer found in a quarter of all breast cancer cases. Precise testing of HER-2 will impact treatment response.Based on the updated American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) HER-2 testing guidelines, we report 141 cases of positive concordance rate between HER-2 IHC stain and dual-probe ISH for HER-2 testing classified in equivocal (2+) and positive (3+) IHC groups in Nakhon Pathom Hospital, Thailand. Our study showed statistical significance in the relationship between positive (3+) IHC and dual-probe ISH for HER-2 testing with a correlation rate of 91.76% (rs = 0.38031, p < 0.0001) and 37.50% in equivocal (2+) IHC groups.This is the first report of a positive concordance rate between equivocal and positive HER-2 IHC and dual-probe ISH for HER-2 based on the ASCO/CAP 2018 guidelines in Thailand. Our study confirmed a statistically significant relationship in the positive IHC (3+) group. In addition, we suggested reflexing ISH testing only in equivocal IHC (2+) cases to decrease the waiting time and economical approach.