The multigene classifiers 95GC/42GC/155GC for precision medicine in ER-positive HER2-negative early breast cancer

Validation of late recurrence prediction by gene expression profiles and clinicopathological factors in estrogen receptor-positive breast cancer

BACKGROUND

The mechanism of late recurrence (LR) of estrogen receptor (ER)-positive breast cancer remains unclear, as previous studies have separately investigated "gene expression profiles" and "clinicopathological factors." Thus, this study aimed to evaluate the predictive capability of LR by combining the two independent factors of gene expression profiles (42-gene classifier: 42GC) and clinicopathological factors (Clinical Treatment Score post-5 years: CTS5) in multiple large cohorts.

METHODS

We analyzed microarray CEL file data downloaded from public databases of 28 global cohorts. A total of 2,454 patients with ER-positive breast cancer were analyzed for 42GC, and 1,263 of these, with complete clinicopathological data were analyzed for CTS5.

RESULTS

In the analysis of recurrent patients, the 42GC LR and CTS5 low-risk group tended to have LR. Notably, in the analysis of patients with and without recurrence, the highest LR rate beyond 5 years was observed in the CTS5 high-risk group. The combination of the 42GC and CTS5 high-risk groups showed the highest LR rate (16.9%), significantly exceeding that of the 42GC non-LR (NLR) and CTS5 low-risk combination (5.41%) (p = 0.038, odds ratio = 3.53). Furthermore, incorporating a third factor, 95GC, potentially reduced the number of patients prioritized for extended hormonal therapy for approximately one-quarter of patients.

CONCLUSIONS

Results confirmed that the two factors, gene expression profiles and clinicopathological factors, affect the time of recurrence. It also showed that the biological predisposition for LR (CTS5 low-risk) differed from the high LR rate (CTS5 high-risk). In clinical practice, patients with the 42GC LR and CTS5 high-risk combination should be prioritized for extended hormonal therapy. The addition of CTS5 and 95GC to 42GC allows for better risk classification of LR.

Convenient determination of serum HER-2 status in breast cancer patients using Raman spectroscopy

Given the significant therapeutic efficacy of anti-HER-2 treatment, the HER-2 status is a crucial piece of information that must be obtained in breast cancer patients. Currently, as per guidelines, HER-2 status is typically acquired from breast tissue of patients. However, there is growing interest in obtaining HER-2 status from serum and other samples due to the convenience and potential for dynamic monitoring. In this study, we have developed a serum Raman spectroscopy technique that allows for the rapid acquisition of HER-2 status in a convenient manner. The established HER-2 negative and positive classification model achieved an area under the curve of 0.8334. To further validate the reliability of our method, we replicated the process using immunohistochemistry and in situ hybridization. The results demonstrate that serum Raman spectroscopy, coupled with artificial intelligence algorithms, is an effective technical approach for obtaining HER-2 status.

Multi-gene assay 95- and 155-gene classifiers for prognosis prediction and chemotherapy omission in lymphnode positive luminal-type breast cancer

BACKGROUND

The prognosis of lymphnode positive breast cancer is worse than that of lymph node negative breast cancer but some cases may not require chemotherapy. We investigated the ability of the new multi-gene assays, 95GC and 155GC, to identify patients with lymphnode positive Luminal-type breast cancer whose chemotherapy can be omitted relatively safely.

PATIENTS AND METHODS

We extracted 1721 cases of lymphnode positive Luminal-type breast cancer from 22 public database Caucasoid cohorts and 3 Asian cohorts, and performed recurrence prognosis analysis with 95GC and 155GC.

RESULTS

Using 95GC, the cases were stratified as the high (n = 917) and low (n = 202) groups according to the prognosis of lymphnode positive Luminal-type endocrine only breast cancer. The 5 years DRFS in the low risk group was relatively good at 90%, and no additional effect of chemotherapy was observed, suggesting omission of chemotherapy. The recurrence prognosis was also significantly dichotomized into the high and low risks by 95GC in 21GC RS 0-25 cases. Here, we found a group with poor prognosis even in post-menopause RS 0-25 and requiring chemotherapy. Additionally, a group in which the prognosis was good in pre-menopause RS 0-25, and the omission of chemotherapy could be considered. Patients in the high-risk group at 155GC had poor prognosis after chemotherapy. 155GC also showed a group that chemotherapy alone was not sufficient.

CONCLUSION

In this study, we demonstrated the possibility of accurately selecting patient groups for which chemotherapy can be omitted from lymphnode positive Luminal-type breast cancer.

Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis

Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.

Oncofertility and Reproductive Counseling in Patients with Breast Cancer: A Retrospective Study

Introduction. Improving the prognosis of breast cancer patients is of utmost importance in terms of increasing survival rates. Modern medicine has therefore prioritized better quality of life for patients, even after the disease, through a better management of the potential long-term side effects induced by anticancer treatments. Fertility preservation and family planning are therefore crucial issues to be addressed in all cancer patients of reproductive age. Along those lines, a new branch of medicine with distinct multidisciplinary characteristics has developed over the years: oncofertility. Although both national and international guidelines value reproductive counseling as an essential aspect of the diagnostic-therapeutic pathway, part and parcel of the informed consent process, it is not included within the protocols adopted by the operating units for the care and management of neoplastic diseases. Objective. This study aimed to evaluate the activity of the Breast Unit of the Policlinico Umberto I Hospital, Rome, Italy, and the degree of compliance with guidelines. By knowing the strengths and weaknesses of such approaches, the standards of care offered to breast cancer patients can be improved. Materials and methods. A retrospective study based on a review of medical records was conducted between 2014 and 2021. Patients under 40 years of age diagnosed with non-metastatic malignancies were included who received chemotherapy treatment, namely neoadjuvant, adjuvant or adjuvant hormone therapy. Results. The data were extracted from the medical records of 51 patients who met the inclusion criteria, 41% of whom received reproductive counseling, and of these, 43% decided to undertake a path of fertility preservation. Factors such as the absence of children and young age reportedly favored both the interest in counseling proposals by the medical staff and the decision to undertake a path of fertility preservation. Conclusions. The study shows that there has been growing interest in the topic of oncofertility, especially in light of law 219/2017. Therefore, since 2018, multiple proposals for reproductive counseling have been set forth, but there was not an equally growing demand for fertility preservation practices, which can be explained by the invasive nature of such practices, the patients’ concern about their own state of health, and poor or inadequate information. Such impediments highlight the importance of standardized counseling and the need for a multidisciplinary medical team to support the patient in the decision-making process. The study also revealed a drop in the number of patients receiving counseling due to the COVID-19 pandemic, contrary to the positive trend that was recorded prior to the pandemic.

The multigene classifiers 95GC/42GC/155GC for precision medicine in ER-positive HER2-negative early breast cancer

In clinical decision‐making, to decide the indication for adjuvant chemotherapy for estrogen receptor‐positive (ER+), human epidermal growth factor receptor‐2‐negative (HER2−), and node‐negative (n0) breast cancer patients, the accurate estimation of recurrence risk is essential. Unfortunately, conventional prognostic factors, such as tumor size, histological grade and ER, progesterone receptor (PR), and HER2 status as well as Ki67 index, are not sufficiently accurate for such estimation. Therefore, several multigene assays (MGAs) based on the mRNA expression analysis of multiple genes in tumor tissue have been developed to better predict patient prognosis. These assays include Oncotype DX, MammaPrint, PAM50, GGI, EndoPredict, and BCI. We developed Curebest™ 95‐Gene Classifier Breast (95GC) classifier, which is unique in that mRNA expression data of all 20 000 human genes are secondarily obtainable, as the 95GC assay is performed using Affymetrix microarray. This can capture mRNA expression of not only 95 genes but also every gene at once, and such gene expression data can be utilized by the other MGAs that we have developed, such as the 155GC, which is used for the prognostic prediction of ER+/HER2− breast cancer patients treated with neoadjuvant chemotherapy. We also developed the 42GC for predicting late recurrence in ER+/HER2− breast cancer patients. In this mini‐review, our recent attempt at the development of various MGAs, which is expected to facilitate the implementation of precision medicine in ER+/HER2− breast cancer patients, is presented with a special emphasis on 95GC.