Gene-expression signatures to inform neoadjuvant treatment decision in HR+/HER2- breast cancer: Available evidence and clinical implications

Tailoring neoadjuvant systemic therapy in breast cancer: "The advent of a personalized approach"-The Breast-Gynecological and Immuno-Oncology International Cancer Conference (BGICC) consensus and recommendations

BACKGROUND

The management of early breast cancer (BC) has witnessed an uprise in the use of neoadjuvant therapy and a remarkable reshaping of the systemic therapy postneoadjuvant treatment in the last few years, with the evolution of many controversial clinical situations that require consensus.

METHODS

During the 14th Breast-Gynecological and Immuno-Oncology International Cancer Conference held in Egypt in 2022, a panel of 44 BC experts from 13 countries voted on statements concerning debatable challenges in the neo/adjuvant treatment setting. The recommendations were subsequently updated based on the most recent data emerging. A modified Delphi approach was used to develop this consensus. A consensus was achieved when ≥75% of voters selected an answer.

RESULTS AND CONCLUSIONS

The consensus recommendations addressed different escalation and de-escalation strategies in the setting of neoadjuvant therapy for early BC. The recommendations recapitulate the available clinical evidence and expert opinion to individualize patient management and optimize therapy outcomes. Consensus was reached in 63% of the statements (52/83), and the rationale behind each statement was clarified.

Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with signifinder Bioconductor package

Understanding cancer mechanisms, defining subtypes, predicting prognosis and assessing therapy efficacy are crucial aspects of cancer research. Gene-expression signatures derived from bulk gene expression data have played a significant role in these endeavors over the past decade. However, recent advancements in high-resolution transcriptomic technologies, such as single-cell RNA sequencing and spatial transcriptomics, have revealed the complex cellular heterogeneity within tumors, necessitating the development of computational tools to characterize tumor mass heterogeneity accurately. Thus we implemented signifinder, a novel R Bioconductor package designed to streamline the collection and use of cancer transcriptional signatures across bulk, single-cell, and spatial transcriptomics data. Leveraging publicly available signatures curated by signifinder, users can assess a wide range of tumor characteristics, including hallmark processes, therapy responses, and tumor microenvironment peculiarities. Through three case studies, we demonstrate the utility of transcriptional signatures in bulk, single-cell, and spatial transcriptomic data analyses, providing insights into cell-resolution transcriptional signatures in oncology. Signifinder represents a significant advancement in cancer transcriptomic data analysis, offering a comprehensive framework for interpreting high-resolution data and addressing tumor complexity.

Major pathologic response and long-term clinical benefit in hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer after neoadjuvant chemotherapy

BACKGROUND

The majority of HR+/HER2-breast cancer patients can also achieve long-term survival despite not attaining pCR, indicating limited prognostic value of pCR in this population. This study aimed to identify novel pathologic end points for predicting long-term outcomes in HR+/HER2-breast cancer after neoadjuvant chemotherapy.

METHODS

We analyzed HR+/HER2-breast cancer patients with stage II-III tumors who underwent curative surgery after neoadjuvant chemotherapy from three hospitals. Major pathologic response (MPR), defined as the presence of Miller-Payne grades 3-5 and positive lymph node ratio of ≤10 %, was used as a pathological evaluation indicator. We assessed the association between MPR and event-free survival (EFS) and performed Multivariable Cox regression to identify independent factors associated with EFS.

RESULTS

From January 2010 to December 2020, 386 patients were included in the final analysis. 28 patients (7.3 %) achieved pCR and 118 patients (30.6 %) achieved MPR. The median duration of follow-up was 54.4 months,5-year EFS was 87 % in the MPR group vs. 68 % in the non-MPR group. Multivariate analysis showed that low PR expression, high clinical stage, lower Miller-Payne grades and Positive lymph node ratio were independent poor prognostic factors for EFS (all P values < 0.05). The prognostic effect of MPR remained in multivariable models (hazard ratio (HR), 0.45; 95 % confidence interval (CI), 0.26-0.76; P = 0.008), In non-pCR patients, those who achieved MPR exhibited a similar EFS compared with pCR patients (HR, 2.25; 95 % CI, 0.51-9.84; P = 0.28).

CONCLUSION

MPR may be a novel pathologic end point in HR+/HER2-breast cancer after neoadjuvant chemotherapy, holding greater applicability in the prognosis evaluation than pCR.

Selecting postoperative adjuvant systemic therapy for early-stage breast cancer: An updated assessment and systematic review of leading commercially available gene expression assays

Gene expression assays (GEAs) can guide treatment for early-stage breast cancer. Several large prospective randomized clinical trials, and numerous additional studies, now provide new information for selecting an appropriate GEA. This systematic review builds upon prior reviews, with a focus on five widely commercialized GEAs (Breast Cancer Index®, EndoPredict®, MammaPrint®, Oncotype DX®, and Prosigna®). The comprehensive dataset available provides a contemporary opportunity to assess each GEA's utility as a prognosticator and/or predictor of adjuvant therapy benefit.

Gene Expression Assays to Tailor Adjuvant Endocrine Therapy for HR+/HER2- Breast Cancer

Adjuvant endocrine therapy (ET) represents the standard of care for almost all hormone receptor (HR)+/HER2- breast cancers, and different agents and durations are currently available. In this context, the tailoring and optimization of adjuvant endocrine treatment by reducing unnecessary toxic treatment while taking into account the biological heterogeneity of HR+/HER2- breast cancer represents a clinical priority. There is therefore a significant need for the integration of biological biomarkers in the choice of adjuvant ET beyond currently used clinicopathological characteristics. Several gene expression assays have been developed to identify patients with HR+/HER2- breast cancer who will not derive benefit from the addition of adjuvant chemotherapy. By enhancing risk stratification and predicting therapeutic response, genomic assays have also shown to be a promising tool for optimizing endocrine treatment decisions. In this study, we review evidence supporting the use of most common commercially available gene expression assays [Oncotype DX, MammaPrint, Breast Cancer Index (BCI), Prosigna, and EndoPredict] in tailoring adjuvant ET. Available data on the use of genomic tests to inform extended adjuvant treatment choice based on the risk of late relapse and on the estimated benefit of a prolonged ET are discussed. Moreover, preliminary evidence regarding the use of genomic assays to inform de-escalation of endocrine treatment, such as shorter durations or omission, for low-risk patients is reviewed. Overall, gene expression assays are emerging as potential tools to further personalize adjuvant treatment for patients with HR+/HER2- breast cancers.

The Evolving Role of Genomic Testing in Early Breast Cancer: Implications for Diagnosis, Prognosis, and Therapy

Multigene prognostic genomic assays have become indispensable in managing early breast cancer (EBC), offering crucial information for risk stratification and guiding adjuvant treatment strategies in conjunction with traditional clinicopathological parameters. The American Society of Clinical Oncology (ASCO) guidelines endorse these assays, though some clinical contexts still lack definitive recommendations. The dynamic landscape of EBC management demands further refinement and optimization of genomic assays to streamline their incorporation into clinical practice. The breast cancer community is poised at the brink of transformative advances in enhancing the clinical utility of genomic assays, aiming to significantly improve the precision and effectiveness of both diagnosis and treatment for women with EBC. This article methodically examines the testing methodologies, clinical validity and utility, costs, diagnostic frameworks, and methodologies of the established genomic tests, including the Oncotype Dx Breast Recurrence Score®, MammaPrint, Prosigna®, EndoPredict®, and Breast Cancer Index (BCI). Among these tests, Prosigna and EndoPredict® have at present been validated only on a prognostic level, while Oncotype Dx, MammaPrint, and BCI hold both a prognostic and predictive role. Oncologists and pathologists engaged in the management of EBC will find in this review a thorough comparison of available genomic assays, as well as strategies to optimize the utilization of the information derived from them.

Neo-adjuvant therapies for ER positive/HER2 negative breast cancers: from chemotherapy to hormonal therapy, CDK inhibitors, and beyond

INTRODUCTION

Chemotherapy has been traditionally used as neo-adjuvant therapy in breast cancer for down-staging of locally advanced disease in all sub-types. In the adjuvant setting, genomic assays have shown that a significant proportion of ER positive/HER2 negative patients do not derive benefit from the addition of chemotherapy to adjuvant endocrine therapy. An interest in hormonal treatments as neo-adjuvant therapies in ER positive/HER2 negative cancers has been borne by their documented success in the adjuvant setting. Moreover, cytotoxic chemotherapy is less effective in ER positive/HER2 negative disease compared with other breast cancer subtypes in obtaining pathologic complete responses.

AREAS COVERED

Neo-adjuvant therapies for ER positive/HER2 negative breast cancers and associated biomarkers are reviewed, using a Medline survey. A focus of discussion is the prediction of patients that are unlikely to derive extra benefit from chemotherapy and have the highest probabilities of benefiting from hormonal and other targeted therapies.

EXPERT OPINION

Predictive biomarkers of response to neo-adjuvant chemotherapy and hormonal therapies are instrumental for selecting ER positive/HER2 negative breast cancer patients for each treatment. Chemotherapy remains the standard of care for many of those patients requiring neo-adjuvant treatment, but other neo-adjuvant therapies are increasingly used.

A Novel Albumin-Related Nutrition Biomarker Predicts Breast Cancer Prognosis in Neoadjuvant Chemotherapy: A Two-Center Cohort Study

BACKGROUND

Recently, there has been a growing focus on the prognostic significance of nutrition-related biomarkers. We attempted to explore the association between a novel albumin-related nutrition marker called "lymphocyte × albumin (LA)" and disease-free survival (DFS) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC).

METHODS

In total, 711 non-metastatic breast cancer patients who underwent NAC at two medical centers were retrospectively analyzed. We performed least absolute shrinkage and selection operator (LASSO) Cox regression analysis as well as multivariate Cox regression analyses to identify the variables associated with DFS and to establish a predictive nomogram.

RESULTS

The nomogram incorporated four variables based on the multivariate analysis of DFS in the training cohort: LA, ypN stage, ypT stage, and hormone receptor status. In comparison with the traditional TNM staging system, the nomogram demonstrated superior discrimination, calibration ability, and clinical usefulness in both the training set and internal and external validation sets. Furthermore, patients stratified into different risk groups resulted in significant differences in DFS.

CONCLUSIONS

LA is an independent prognostic biomarker, and LA-based prognostic nomogram offers a more precise assessment of DFS for breast cancer patients treated with NAC, potentially serving as a valuable tool for personalized prognostic predictions.

Appraisal of Systemic Treatment Strategies in Early HER2-Positive Breast Cancer-A Literature Review

BACKGROUND

The overexpression of the human epidermal growth factor receptor 2 (HER2+) accounts for 15-20% of all breast cancer phenotypes. Even after the completion of the standard combination of chemotherapy and trastuzumab, relapse events occur in approximately 15% of cases. The neoadjuvant approach has multiple benefits that include the potential to downgrade staging and convert previously unresectable tumors to operable tumors. In addition, achieving a pathologic complete response (pCR) following preoperative systemic treatment is prognostic of enhanced survival outcomes. Thus, optimal evaluation among the suitable strategies is crucial in deciding which patients should be selected for the neoadjuvant approach.

METHODS

A literature search was conducted in the Embase, Medline, and Cochrane electronic libraries.

CONCLUSION

The evaluation of tumor and LN staging and, hence, stratifying BC recurrence risk are decisive factors in guiding clinicians to optimize treatment decisions between the neoadjuvant versus adjuvant approaches. For each individual case, it is important to consider the most likely postsurgical outcome, since, if the patient does not obtain pCR following neoadjuvant treatment, they are eligible for adjuvant T-DM1 in the case of residual disease. This review of HER2-positive female BC outlines suitable neoadjuvant and adjuvant systemic treatment strategies for guiding clinical decision making around the selection of an appropriate therapy.

A prospective cohort study identifying radiologic and tumor related factors of importance for breast conserving surgery after neoadjuvant chemotherapy

INTRODUCTION

Neoadjuvant chemotherapy (NAC) is an established treatment option for early breast cancer, potentially downstaging the tumor and increasing the eligibility for breast-conserving surgery (BCS). The primary aim of this study was to assess the rate of BCS after NAC, and the secondary aim was to identify predictors of application of BCS after NAC.

MATERIALS AND METHODS

This was an observational prospective cohort study of 226 patients in the SCAN-B (Clinical Trials NCT02306096) neoadjuvant cohort during 2014-2019. Eligibility for BCS was assessed at baseline and after NAC. Uni- and multivariable logistic regression analyses were performed using covariates with clinical relevance and/or those associated with outcome (BCS versus mastectomy), including tumor subtype, by gene expression analysis.

RESULTS

The overall BCS rate was 52%, and this rate increased during the study period (from 37% to 52%). Pathological complete response was achieved in 69 patients (30%). Predictors for BCS were smaller tumor size on mammography, visibility on ultrasound, histological subtype other than lobular, benign axillary status, and a diagnosis of triple-negative or HER2-positive subtype, with a similar trend for gene expression subtypes. Mammographic density was negatively related to BCS in a dose-response pattern. In the multivariable logistic regression model, tumor stage at diagnosis and mammographic density showed the strongest association with BCS.

CONCLUSION

The rate of BCS after NAC increased during the study period to 52%. With modern treatment options for NAC the potential for tumor response and BCS eligibility might further increase.

signifinder enables the identification of tumor cell states and cancer expression signatures in bulk, single-cell and spatial transcriptomic data

Over the last decade, many studies and some clinical trials have proposed gene expression signatures as a valuable tool for understanding cancer mechanisms, defining subtypes, monitoring patient prognosis, and therapy efficacy. However, technical and biological concerns about reproducibility have been raised. Technical reproducibility is a major concern: we currently lack a computational implementation of the proposed signatures, which would provide detailed signature definition and assure reproducibility, dissemination, and usability of the classifier. Another concern regards intratumor heterogeneity, which has never been addressed when studying these types of biomarkers using bulk transcriptomics. With the aim of providing a tool able to improve the reproducibility and usability of gene expression signatures, we propose signifinder, an R package that provides the infrastructure to collect, implement, and compare expression-based signatures from cancer literature. The included signatures cover a wide range of biological processes from metabolism and programmed cell death, to morphological changes, such as quantification of epithelial or mesenchymal-like status. Collected signatures can score tumor cell characteristics, such as the predicted response to therapy or the survival association, and can quantify microenvironmental information, including hypoxia and immune response activity. signifinder has been used to characterize tumor samples and to investigate intra-tumor heterogeneity, extending its application to single-cell and spatial transcriptomic data. Through these higher-resolution technologies, it has become increasingly apparent that the single-sample score assessment obtained by transcriptional signatures is conditioned by the phenotypic and genetic intratumor heterogeneity of tumor masses. Since the characteristics of the most abundant cell type or clone might not necessarily predict the properties of mixed populations, signature prediction efficacy is lowered, thus impeding effective clinical diagnostics. Through signifinder, we offer general principles for interpreting and comparing transcriptional signatures, as well as suggestions for additional signatures that would allow for more complete and robust data inferences. We consider signifinder a useful tool to pave the way for reproducibility and comparison of transcriptional signatures in oncology.

Competing Endogenous RNA Regulatory Networks of hsa_circ_0126672 in Pathophysiology of Coronary Heart Disease

Coronary heart disease (CHD) is a global health concern, and its molecular origin is not fully elucidated. Dysregulation of ncRNAs has been linked to many metabolic and infectious diseases. This study aimed to explore the role of circRNAs in the pathogenesis of CHD and predicted a candidate circRNA that could be targeted for therapeutic approaches to the disease. circRNAs associated with CHD were identified and CHD gene expression profiles were obtained, and analyzed with GEO2R. In addition, differentially expressed miRNA target genes (miR-DEGs) were identified and subjected to functional enrichment analysis. Networks of circRNA/miRNA/mRNA and the miRNA/affected pathways were constructed. Furthermore, a miRNA/mRNA homology study was performed. We identified that hsa_circ_0126672 was strongly associated with the CHD pathology by competing for endogenous RNA (ceRNA) mechanisms. hsa_circ_0126672 characteristically sponges miR-145-5p, miR-186-5p, miR-548c-3p, miR-7-5p, miR-495-3p, miR-203a-3p, and miR-21. Up-regulation of has_circ_0126672 affected various CHD-related cellular functions, such as atherosclerosis, JAK/STAT, and Apelin signaling pathways. Our results also revealed a perfect and stable interaction for the hybrid of miR-145-5p with NOS1 and RPS6KB1. Finally, miR-145-5p had the highest degree of interaction with the validated small molecules. Henchashsa_circ_0126672 and target miRNAs, notably miR-145-5p, could be good candidates for the diagnosis and therapeutic approaches to CHD.

Neoadjuvant endocrine therapy in postmenopausal women with HR+/HER2- breast cancer

INTRODUCTION

While endocrine therapy is the standard-of-care adjuvant treatment for hormone receptor-positive (HR+) breast cancers, there is also extensive evidence for the role of pre-operative (or neoadjuvant) endocrine therapy (NET) in HR+ postmenopausal women.

AREAS COVERED

We conducted a thorough review of the published literature, to summarize the evidence to date, including studies of how NET compares to neoadjuvant chemotherapy, which NET agents are preferable, and the optimal duration of NET. We describe the importance of on-treatment assessment of response, the different predictors available (including Ki67, PEPI score, and molecular signatures) and the research opportunities the pre-operative setting offers. We also summarize recent combination trials and discuss how the COVID-19 pandemic led to increases in NET use for safe management of cases with deferred surgery and adjuvant treatments.

EXPERT OPINION

NET represents a safe and effective tool for the management of postmenopausal women with HR+/HER2- breast cancer, enabling disease downstaging and a wider range of surgical options. Aromatase inhibitors are the preferred NET, with evidence suggesting that longer regimens might yield optimal results. However, NET remains currently underutilised in many territories and institutions. Further validation of predictors for treatment response and benefit is needed to help standardise and fully exploit the potential of NET in the clinic.

Multigene signatures for early breast cancer in clinical practice: A report of the Lombardy genomic assays for breast cancer working group

The increasing understanding of breast cancer biology has provided the basis for the development of multigene signatures aimed to improve the capability of clinicians to assess patients' prognostication and risk stratification. Incorporating these tools in clinical practice has profoundly impacted on the decision-making process for the adjuvant therapy of patients with ER+/HER2- early breast cancer and the results from prospective adjuvant trials have strengthened the clinical utility of multigene signatures in this setting. In July 2019, Lombardy was the first Region in Italy to reimburse genomic testing for patients with ER+/HER2- early breast cancer. Three years later, a group of investigators from six referral Cancer Centers in Lombardy convened to debate the use of multigene signatures in clinical practice and share their own experience with the tests after reimbursement. Here, we reviewed relevant data on the role of multigene signatures in tailoring adjuvant chemotherapy for patients with ER+/HER2- early breast cancer and discussed about the optimal use of these assays in current clinical practice. As the treatment landscape of early breast cancer evolves and novel questions about the possible additional applications of multigene assays arise, we also provide our viewpoint on the potential implementation of the assays in the evolving scenario ER+/HER2- early breast cancer treatment.

Controversies and Opportunities in the Clinical Daily Use of the 21-Gene Assay for Prognostication and Prediction of Chemotherapy Benefit in HR+/HER2- Early Breast Cancer

Several multigene assays have been developed to help clinicians in defining adjuvant treatment for patients with hormone-receptor-positive (HR+), human epidermal growth factor receptor-2 (HER2)-negative early breast cancer. Despite the 21-gene assay having been available for decades, it has only recently been included in the healthcare systems of several countries. Clinical optimisation of the test remains of critical interest to achieve a greater impact of genomic information in HR+/HER2- early breast cancer. Although current guidelines recommend the use of the 21-gene assay in early breast cancer at intermediate risk of relapse, the implication of the Recurrence Score (RS) in some grey areas still remains uncertain. Our aim is to critically discuss the role of RS in peculiar circumstances. In particular, we focus on the complex integration of genomic data with clinicopathological factors; the potential clinical impact of RS in node-positive premenopausal women and in the neoadjuvant setting; the significance of RS in special histologies and in male patients; and the management and time-optimisation of test ordering. In the absence of robust evidence in these areas, we provide perspectives for improving the use of the 21-gene assay in the decision-making process and guide adjuvant treatment decisions even in challenging cases.

EIF4A3-induced circBRWD3 promotes tumorigenesis of breast cancer through miR-142-3p_miR-142-5p/RAC1/PAK1 signaling

CircBRWD3 is a newly discovered circRNA, and its potential function has not been probed. Here, we aimed to molecularly dissect the role of circBRWD3 in the tumorigenesis and progression of breast cancer (BC). qRT-PCR analysis revealed that circBRWD3 expression was dramatically upregulated in BC tissues, a feature that was positively correlated with the poor prognosis of patients with BC. CircBRWD3 knockdown repressed cell proliferation and metastasis, while promoting cell apoptosis in vitro. Consistently, an in vivo circBRWD3 deficiency model exhibited suppressed tumor metastasis and oncogenesis. On the other hand, circBRWD3 overexpression promoted cancer cell activity and tumorigenesis. Further, mechanistic studies elucidated that circBRWD3 sponged both miR-142-3p and miR-142-5p to modulate RAC1 expression, which subsequently activated the RAC1/PAK1 signaling to facilitate the tumorigenesis and progression of BC. Moreover, we discovered that EIF4A3 facilitated circBRWD3 expression by targeting the upstream of BRWD3 pre-mRNA. In conclusion, our study reveals that circBRWD3 facilitates BC tumorigenesis by regulating the circBRWD3/miR-142-3p_miR-142-5p /RAC1/PAK1 axis. In addition, circBRWD3 expression is positively regulated by an RNA-binding protein, EIFA3. Our results provide valuable scientific data for early diagnosis and therapy for breast cancer patients.

Modulation of Small RNA Signatures by Astrocytes on Early Neurodegeneration Stages; Implications for Biomarker Discovery

Diagnosis of neurodegenerative disease (NDD) is complex, therefore simpler, less invasive, more accurate biomarkers are needed. small non-coding RNA (sncRNA) dysregulates in NDDs and sncRNA signatures have been explored for the diagnosis of NDDs, however, the performance of previous biomarkers is still better. Astrocyte dysfunction promotes neurodegeneration and thus derived scnRNA signatures could provide a more precise way to identify of changes related to NDD course and pathogenesis, and it could be useful for the dissection of mechanistic insights operating in NDD. Often sncRNA are transported outside the cell by the action of secreted particles such as extracellular vesicles (EV), which protect sncRNA from degradation. Furthermore, EV associated sncRNA can cross the BBB to be found in easier to obtain peripheral samples, EVs also inherit cell-specific surface markers that can be used for the identification of Astrocyte Derived Extracellular Vesicles (ADEVs) in a peripheral sample. By the study of the sncRNA transported in ADEVs it is possible to identify astrocyte specific sncRNA signatures that could show astrocyte dysfunction in a more simpler manner than previous methods. However, sncRNA signatures in ADEV are not a copy of intracellular transcriptome and methodological aspects such as the yield of sncRNA produced in ADEV or the variable amount of ADEV captured after separation protocols must be considered. Here we review the role as signaling molecules of ADEV derived sncRNA dysregulated in conditions associated with risk of neurodegeneration, providing an explanation of why to choose ADEV for the identification of astrocyte-specific transcriptome. Finally, we discuss possible limitations of this approach and the need to improve the detection limits of sncRNA for the use of ADEV derived sncRNA signatures.

ERCC1 is a potential biomarker for predicting prognosis, immunotherapy, chemotherapy efficacy, and expression validation in HER2 over-expressing breast cancer

Objective

To investigate the relationship between Excision repair cross-complementation 1 (ERCC1) expression, clinicopathological features, and breast cancer prognosis in patients treated with trastuzumab. Further, we aim to explore the immune status of ERCC1 in breast cancer.

Methods

The data were retrieved from publicly available databases like the Cancer Genome Atlas, Therapeutically Applicable Research to Generate Effective Treatments, and the Genotype-Tissue Expression. The data was used to perform differential expression analyses between tumor and normal tissues in pan-cancers, immune-related analysis, homologous recombination deficiency (HRD), tumor mutation burden, and microsatellite instability. A total of 210 patients with HER2 over-expressing breast cancer from the Fourth Hospital of Hebei Medical University between January 2013 to December 2015 were enrolled in the study. Ten adjacent normal tissues were used to study the expression pattern of ERCC1 in normal tissues. Immunohistochemistry was performed to study ERCC1 expression and immune cell infiltration in different status of ERCC1 expression. Further, the correlation between ERCC1 expression, immune cell infiltration clinicopathological features, and the prognosis of patients with breast cancer was analyzed.

Results

The immune analysis revealed a significant correlation between CD8+ T cell, CD4+ T cell, T helper cell, macrophages, mast cells, and ERCC1 expression. Spearman analysis show that ERCC1 expression is related to macrophages and T cells. A close correlation was observed between increased ERCC1 expression and high tumor immune dysfunction and exclusion (TIDE) score as well as HRD. The results revealed a significant correlation among ERCC1, chemotherapy and estrogen receptor (ER; P < 0.05) expression. Univariate survival analysis revealed a significant correlation (P < 0.05) between that ERCC1 and ER expression, blood vessel invasion, and disease-free survival (DFS). ERCC1 and ER expression, tumor size, blood vessel invasion, pathological type, and lymph node metastases significantly correlated (P < 0.05) with overall survival in patients. Multivariate regression analysis revealed that ERCC1 expression and chemotherapy were independent factors that influence DFS. ERCC1 expression and vascular tumor thrombus were independent influencing factors that influence OS.

Conclusion

A correlation was observed between high ERCC1 expression and poor patient prognosis. High ERCC1 expression also influences the efficacy of immunotherapy and chemotherapy.

Breast microbiome associations with breast tumor characteristics and neoadjuvant chemotherapy: A case-control study

Background

Commensal microbiota have been proven to colonize the mammary gland, but whether their composition is altered in patients with breast cancer (BC) remains elusive. This study intends to explore the breast microbiome differences between benign and malignant diseases and to investigate the impact of neoadjuvant chemotherapy (NAC) on the breast microbiota in patients with BC.

Methods

Breast normal adipose tissues (NATs) were collected from 79 patients with BC and 15 controls between July 2019 and November 2021. The BC group consisted of 29 patients who had received NAC and 50 who were non-NAC patients. Participants diagnosed with benign breast disease were recruited as controls. 16S rRNA gene sequencing was used to analyze the bacterial diversity of NATs.

Results

The community structure of the NAT microbiome was significantly different between the BC and control groups. Proteobacteria decreased (47.40% versus 39.74%), whereas Firmicutes increased (15.71% versus 25.33%) in patients with BC when compared with that in control tissues. Nine genera were enriched in BC NATs, and four genera levels increased in the control group. The associations between differential bacterial genera and breast tumor grade were calculated by Spearman’s correlation. The results showed that tumor grade was positively associated with the relative abundance of Streptococcus and negatively related to Vibrio, Pseudoalteromonas, RB41, and Photobacterium. Moreover, menopause was associated with the microbiota composition change of non-NAC BC patients and related to the significant reduction in the abundance level of Pseudoalteromonas, Veillonella, and Alcaligenes. In addition, NAC was related to the beta diversity of patients with BC and associated with the decrease of Clostridium_sensu_stricto_7 and Clostridium_sensu_stricto_2 in postmenopausal patients. Of note, Tax4Fun functional prediction analysis revealed that the metabolic state was more exuberant in the BC group with upregulating of multiple metabolism-related pathways.

Conclusion

Our results offer new insight into the relationship between NAC and breast microbiota and help to better characterize the breast microbial dysbiosis that occurs in patients with BC. Further epidemiological studies with larger sample size and well-designed animal experiments are required to elucidate the role of breast microbiota in the therapeutic outcome of BC.

Clinical utility of PDX cohorts to reveal biomarkers of intrinsic resistance and clonal architecture changes underlying acquired resistance to cetuximab in HNSCC

Cetuximab is a widely used drug for treating head and neck squamous cell carcinomas (HNSCCs); however, it provides restricted clinical benefits, and its response duration is limited by drug resistance. Here, we conducted randomized “Phase II-like clinical trials” of 49 HNSCC PDX models and reveal multiple informative biomarkers for intrinsic resistance to cetuximab (e.g., amplification of ANKH, up-regulation of PARP3). After validating these intrinsic resistance biomarkers in another HNSCC PDX cohort (61 PDX models), we generated acquired cetuximab resistance PDX models and analyzed them to uncover resistance mechanisms. Whole exome sequencing and transcriptome sequencing revealed diverse patterns of clonal selection in acquired resistant PDXs, including the emergence of subclones with strongly activated RAS/MAPK. Extending these insights, we show that a combination of a RAC1/RAC3 dual-target inhibitor and cetuximab could overcome acquired cetuximab resistance in vitro and in vivo. Beyond revealing intrinsic resistance biomarkers, our PDX-based study shows how clonal architecture changes underlying acquired resistance can be targeted to expand the therapeutic utility of this important drug to more HNSCC patients.

The Clinical Research and Latest Application of Genomic Assays in Early-Stage Breast Cancer

Breast cancer is a kind of malignant tumor that seriously endangers women's life and health. Once diagnosed, most patients will receive a combination of treatments to achieve a cure. However, breast cancer is a heterogeneous disease. Even with the same clinical stage and pathological features, its response to treatment and postoperative recurrence risk may still be completely different. With the advent of genomic assay, some patients with early-stage breast cancer who originally needed treatment can still achieve long-term disease-free survival without adjuvant chemotherapy, so as to achieve personalized and accurate treatment mode to a certain extent. In this paper, we reviewed the 5 most widely used and studied genomic panel technologies in breast cancer, namely Oncotype DX, MammaPrint, RecurIndex, PAM50, and EndoPredict, according to accessibility and availability. Based on the results of the completed or ongoing clinical studies, we summarized the origin, applicable population, and clinical efficacy of each detection method, and discussed the potential development prospect of detection technology in the future.