Prognostic and Predictive Markers for Treatment Decisions in Early Breast Cancer

Is routine axillary staging still required in clinically node negative early breast cancer in women over 74 years?

BACKGROUND

Investigate incidence and identify predictors of axillary lymph node metastases in early breast cancer in women >74 years Australia and New Zealand to inform decision making about sentinel lymph node (SLN) biopsy in this population.

METHODS

Retrospective review of invasive breast cancer in women in Australia and New Zealand between 2010 and 2022 using BreastSurgANZ Quality Audit Database. Data included patient demographics, tumour characteristics, surgery type, axillary nodal status and adjuvant therapy. Descriptive analysis of incidence of axillary nodal metastases and use of adjuvant therapy in various patient and tumour groups was performed, followed by statistical analysis using multivariate logistic regression to identify predictors of axillary nodal positivity and correlation between nodal status and prescription of adjuvant therapy.

RESULTS

Review of 127 436 cases of invasive breast cancer, 17 599 cases >74 years. Two thirds of the overall population and in those >74 years were node negative. In patients >74 years with grade 1-2, T1a-b cancers, ER+/HER2- 94% were node negative. Patient age, tumour size, grade and biomarker profile correlated with axillary nodal status and analysis of adjuvant therapy revealed significant correlation between nodal stage and adjuvant radiotherapy, chemotherapy and endocrine therapy.

CONCLUSION

A total of 94% of patients >74 years with T1a/b, ER positive HER2 negative breast cancer were node negative. Nodal status significantly influences adjuvant treatment in this patient group and therefore, we recommend clinicians consider tumour factors and patient fitness in their decision making about SLN biopsy in the elderly population with hormone receptor positive early breast cancer.

Integration of transcriptomics and machine learning for insights into breast cancer: exploring lipid metabolism and immune interactions

Background

Breast cancer (BRCA) represents a substantial global health challenge marked by inadequate early detection rates. The complex interplay between the tumor immune microenvironment and fatty acid metabolism in BRCA requires further investigation to elucidate the specific role of lipid metabolism in this disease.

Methods

We systematically integrated nine machine learning algorithms into 184 unique combinations to develop a consensus model for lipid metabolism-related prognostic genes (LMPGS). Additionally, transcriptomics analysis provided a comprehensive understanding of this prognostic signature. Using the ESTIMATE method, we evaluated immune infiltration among different risk subgroups and assessed their responsiveness to immunotherapy. Tailored treatments were screened for specific risk subgroups. Finally, we verified the expression of key genes through in vitro experiments.

Results

We identified 259 differentially expressed genes (DEGs) related to lipid metabolism through analysis of the cancer genome atlas program (TCGA) database. Subsequently, via univariate Cox regression analysis and C-index analysis, we developed an optimal machine learning algorithm to construct a 21-gene LMPGS model. We used optimal cutoff values to divide the lipid metabolism prognostic gene scores into two groups according to high and low scores. Our study revealed distinct biological functions and mutation landscapes between high-scoring and low-scoring patients. The low-scoring group presented a greater immune score, whereas the high-scoring group presented enhanced responses to both immunotherapy and chemotherapy drugs. Single-cell analysis highlighted significant upregulation of CPNE3 in epithelial cells. Moreover, by employing molecular docking, we identified niclosamide as a potential targeted therapeutic drug. Finally, our experiments demonstrated high expression of MTMR9 and CPNE3 in BRCA and their significant correlation with prognosis.

Conclusion

By employing bioinformatics and diverse machine learning algorithms, we successfully identified genes associated with lipid metabolism in BRCA and uncovered potential therapeutic agents, thereby offering novel insights into the mechanisms and treatment strategies for BRCA.

Exploring HMMR as a therapeutic frontier in breast cancer treatment, its interaction with various cell cycle genes, and targeting its overexpression through specific inhibitors

Among women, breast carcinoma is one of the most complex cancers, with one of the highest death rates worldwide. There have been significant improvements in treatment methods, but its early detection still remains an issue to be resolved. This study explores the multifaceted function of hyaluronan-mediated motility receptor (HMMR) in breast cancer progression. HMMR's association with key cell cycle regulators (AURKA, TPX2, and CDK1) underscores its pivotal role in cancer initiation and advancement. HMMR's involvement in microtubule assembly and cellular interactions, both extracellularly and intracellularly, provides critical insights into its contribution to cancer cell processes. Elevated HMMR expression triggered by inflammatory signals correlates with unfavorable prognosis in breast cancer and various other malignancies. Therefore, recognizing HMMR as a promising therapeutic target, the study validates the overexpression of HMMR in breast cancer and various pan cancers and its correlation with certain proteins such as AURKA, TPX2, and CDK1 through online databases. Furthermore, the pathways associated with HMMR were explored using pathway enrichment analysis, such as Gene Ontology, offering a foundation for the development of effective strategies in breast cancer treatment. The study further highlights compounds capable of inhibiting certain pathways, which, in turn, would inhibit the upregulation of HMMR in breast cancer. The results were further validated via MD simulations in addition to molecular docking to explore protein-protein/ligand interaction. Consequently, these findings imply that HMMR could play a pivotal role as a crucial oncogenic regulator, highlighting its potential as a promising target for the therapeutic intervention of breast carcinoma.

Biomarkers in Breast Cancer: An Old Story with a New End

Breast cancer is the second most frequent cancer in the world. It is a heterogeneous disease and the leading cause of cancer mortality in women. Advances in molecular technologies allowed for the identification of new and more specifics biomarkers for breast cancer diagnosis, prognosis, and risk prediction, enabling personalized treatments, improving therapy, and preventing overtreatment, undertreatment, and incorrect treatment. Several breast cancer biomarkers have been identified and, along with traditional biomarkers, they can assist physicians throughout treatment plan and increase therapy success. Despite the need of more data to improve specificity and determine the real clinical utility of some biomarkers, others are already established and can be used as a guide to make treatment decisions. In this review, we summarize the available traditional, novel, and potential biomarkers while also including gene expression profiles, breast cancer single-cell and polyploid giant cancer cells. We hope to help physicians understand tumor specific characteristics and support decision-making in patient-personalized clinical management, consequently improving treatment outcome.

RNA disruption is a widespread phenomenon associated with stress-induced cell death in tumour cells

We have previously shown that neoadjuvant chemotherapy can induce the degradation of tumour ribosomal RNA (rRNA) in patients with advanced breast cancer, a phenomenon we termed "RNA disruption". Extensive tumour RNA disruption during chemotherapy was associated with a post-treatment pathological complete response and improved disease-free survival. The RNA disruption assay (RDA), which quantifies this phenomenon, is now being evaluated for its clinical utility in a large multinational clinical trial. However, it remains unclear if RNA disruption (i) is manifested across many tumour and non-tumour cell types, (ii) can occur in response to cell stress, and (iii) is associated with tumour cell death. In this study, we show that RNA disruption is induced by several mechanistically distinct chemotherapy agents and report that this phenomenon is observed in response to oxidative stress, endoplasmic reticulum (ER) stress, protein translation inhibition and nutrient/growth factor limitation. We further show that RNA disruption is dose- and time-dependent, and occurs in both tumourigenic and non-tumourigenic cell types. Northern blotting experiments suggest that the rRNA fragments generated during RNA disruption stem (at least in part) from the 28S rRNA. Moreover, we demonstrate that RNA disruption is reproducibly associated with three robust biomarkers of cell death: strongly reduced cell numbers, lost cell replicative capacity, and the generation of cells with a subG1 DNA content. Thus, our findings indicate that RNA disruption is a widespread phenomenon exhibited in mammalian cells under stress, and that high RNA disruption is associated with the onset of cell death.

Induction of interferon-β and interferon signaling by TRAIL and Smac mimetics via caspase-8 in breast cancer cells

Breast cancer prognosis is frequently good but a substantial number of patients suffer from relapse. The death receptor ligand TRAIL can in combination with Smac mimetics induce apoptosis in some luminal-like ER-positive breast cancer cell lines, such as CAMA-1, but not in MCF-7 cells. Here we show that TRAIL and the Smac mimetic LCL161 induce non-canonical NF-κB and IFN signaling in ER-positive MCF-7 cells and in CAMA-1 breast cancer cells when apoptosis is blocked by caspase inhibition. Levels of p52 are increased and STAT1 gets phosphorylated. STAT1 phosphorylation is induced by TRAIL alone in MCF-7 cells and is independent of non-canonical NF-κB since downregulation of NIK has no effect. The phosphorylation of STAT1 is a rather late event, appearing after 24 hours of TRAIL stimulation. It is preceded by an increase in IFNB1 mRNA levels and can be blocked by siRNA targeting the type I IFN receptor IFNAR1 and by inhibition of Janus kinases by Ruxolitinib. Moreover, downregulation of caspase-8, but not inhibition of caspase activity, blocks TRAIL-mediated STAT1 phosphorylation and induction of IFN-related genes. The data suggest that TRAIL-induced IFNB1 expression in MCF-7 cells is dependent on a non-apoptotic role of caspase-8 and leads to autocrine interferon-β signaling.

Tumor Mutational Patterns and Infiltrating Lymphocyte Density in Young and Elderly Patients With Breast Cancer

BACKGROUND/AIM

Age may pertain to different tumor genotype characteristics which may interfere with treatment efficacy and prognosis. We investigated the distribution and prognostic effect of mutations and tumor infiltrating lymphocyte (stromal TIL density) in young (≤35 years) and elderly (>65 years) early breast cancer patients.

MATERIALS AND METHODS

Paraffin tumor genotypes of all clinical subtypes from 345 patients were examined.

RESULTS

A total of 638 mutations were detected in 221 patients (64.1%). Compared to young, elderly patients presented with lower TIL density (p<0.001) but more TILs in TP53 mutated tumors (p=0.042). Mutation in one, rather than in 2 or more genes, conferred better outcome (DFS: HR=0.51, p=0.016; OS: HR=0.47, p=0.015) but the effect was age-independent.

CONCLUSION

There are fewer TILs and different mutations patterns in tumors from elderly patients compared to young. Age and TIL-independent gene agnostic co-mutations affect patient outcome.

Cancer testis antigens and NY-BR-1 expression in primary breast cancer: prognostic and therapeutic implications

BACKGROUND

Cancer-testis antigens (CTA) comprise a family of proteins, which are physiologically expressed in adult human tissues solely in testicular germ cells and occasionally placenta. However, CTA expression has been reported in various malignancies. CTAs have been identified by their ability to elicit autologous cellular and or serological immune responses, and are considered potential targets for cancer immunotherapy. The breast differentiation antigen NY-BR-1, expressed specifically in normal and malignant breast tissue, has also immunogenic properties. Here we evaluated the expression patterns of CTAs and NY-BR-1 in breast cancer in correlation to clinico-pathological parameters in order to determine their possible impact as prognostic factors.

METHODS

The reactivity pattern of various mAbs (6C1, MA454, M3H67, 57B, E978, GAGE #26 and NY-BR-1 #5) were assessed by immunohistochemistry in a tissue micro array series of 210 randomly selected primary invasive breast cancers in order to study the diversity of different CTAs (e.g. MAGE-A, NY-ESO-1, GAGE) and NY-BR-1. These expression data were correlated to clinico-pathological parameters and outcome data including disease-free and overall survival.

RESULTS

Expression of at least one CTA was detectable in the cytoplasm of tumor cells in 37.2% of the cases. NY-BR-1 expression was found in 46.6% of tumors, respectively. Overall, CTA expression seemed to be linked to adverse prognosis and M3H67 immunoreactivity specifically was significantly correlated to shorter overall and disease-free survival (p=0.000 and 0.024, respectively).

CONCLUSIONS

Our findings suggest that M3H67 immunoreactivity could serve as potential prognostic marker in primary breast cancer patients. The exclusive expression of CTAs in tumor tissues as well as the frequent expression of NY-BR-1 could define new targets for specific breast cancer therapies.