Multigene testing in breast cancer: What have we learned from the 21-gene recurrence score assay?

Exploring novel protein-based biomarkers for advancing breast cancer diagnosis: A review

This review provides a contemporary examination of the evolving landscape of breast cancer (BC) diagnosis, focusing on the pivotal role of novel protein-based biomarkers. The overview begins by elucidating the multifaceted nature of BC, exploring its prevalence, subtypes, and clinical complexities. A critical emphasis is placed on the transformative impact of proteomics, dissecting the proteome to unravel the molecular intricacies of BC. Navigating through various sources of samples crucial for biomarker investigations, the review underscores the significance of robust sample processing methods and their validation in ensuring reliable outcomes. The central theme of the review revolves around the identification and evaluation of novel protein-based biomarkers. Cutting-edge discoveries are summarised, shedding light on emerging biomarkers poised for clinical application. Nevertheless, the review candidly addresses the challenges inherent in biomarker discovery, including issues of standardisation, reproducibility, and the complex heterogeneity of BC. The future direction section envisions innovative strategies and technologies to overcome existing challenges. In conclusion, the review summarises the current state of BC biomarker research, offering insights into the intricacies of proteomic investigations. As precision medicine gains momentum, the integration of novel protein-based biomarkers emerges as a promising avenue for enhancing the accuracy and efficacy of BC diagnosis. This review serves as a compass for researchers and clinicians navigating the evolving landscape of BC biomarker discovery, guiding them toward transformative advancements in diagnostic precision and personalised patient care.

21-gene recurrence score in predicting the outcome of postoperative radiotherapy in T1-2N1 luminal breast cancer after breast-conserving surgery

BACKGROUND

In those with one to three positive lymph nodes (N1) breast cancer (BC), the 21-gene recurrence score (RS) classification can be referred for decision-making on adjuvant chemotherapy. This study aimed to investigate the effect of RS in predicting the survival benefit of postoperative radiotherapy (PORT) in T1-2N1 BC with estrogen receptor-positive and human epidermal growth factor receptor 2-negative disease after breast-conserving surgery (BCS).

METHODS

We included patients with BC and available RS data from the Surveillance, Epidemiology, and End Results Oncotype DX database. The chi-square test, Kaplan-Meier method, propensity score matching (PSM) as well as multivariable Cox proportional hazard analyses were used for statistical analyses.

RESULTS

We included 6509 patients in the analysis. Of these patients, 5302 (85.5%) were treated with BCS + PORT, and 207 (15.5%) had BCS alone. There were 1419 (21.8%), 4319 (66.4%), and 771 (11.8%) patients being low-, intermediate-, and high-risk RS, respectively. After PSM, PORT was significantly associated with a 5-year overall survival (OS) advantage (95.1% vs. 90.5%, P < 0.001) compared to those without PORT, which similar breast cancer-specific survival (BCSS) was found between the treatment arms (P = 0.126). The sensitivity analyses showed that PORT was not associated with a better BCSS (P = 0.472) and OS (P = 0.650) than those without PORT in the low-risk RS cohort. However, PORT was associated with a better BCSS (P = 0.031) and OS (P < 0.001) compared to those without PORT in the intermediate/high-risk RS cohorts.

CONCLUSIONS

Our study highlights the possible role of the RS in predicting the outcome of PORT in T1-2N1 luminal BC patients undergoing BCS.

Increased PI3K pathway activity is associated with recurrent breast cancer in patients with low and intermediate 21-gene recurrence score

AIMS

We investigated key signalling pathways' activity and mutational status of early-stage breast carcinomas with low and intermediate 21-gene recurrence score (RS) to identify molecular features that may predict recurrence.

METHODS

This is a retrospective case-control study of 18 patients with recurrent breast carcinoma with low and intermediate 21-gene RS (<25) and control group of 15 non-recurrent breast cancer patients. DNA and mRNA were extracted from tumour tissue. mRNA expression of genes involved in oestrogen receptor (ER), androgen receptor (AR), PI3K and MAPK signalling pathways was measured by real-time quantitative reverse transcription-qPCR (OncoSIGNal G4 test, InnoSIGN). Tumour mutational landscape was assessed by targeted DNA sequencing (Oncomine Precision Assay).

RESULTS

There were no statistical differences between the groups' demographic and clinicopathological characteristics. PI3K pathway showed significantly higher activity in cases compared with controls (p=0.0014). Receiver operating characteristic curve analysis showed an area under the curve of 0.79 for PI3K pathway activity in the prediction of recurrent disease in low and intermediate 21-gene RS breast cancer. There was no difference in ER, AR and MAPK pathway activity. PIK3CA alterations were the most common driver mutations, but no difference was found between the groups (p=0.46) and no association with PI3K pathway activity (p=0.86). Higher Ki67 gene expression was associated with recurrences (p=0.042) CONCLUSION: Increased PI3K pathway activity, independent of PIK3CA mutations, may play a role in the recurrence of early-stage breast cancer with low and intermediate 21-gene RS. Pathway analysis can help to identify high-risk patients in this setting.

Prediction of prognosis and immune landscape in cervical cancer based on heat shock protein-related genes

Objective: Heat shock proteins (HSPs) play key roles in the malignant transformation and progression of many tumors. However, the effectiveness of using HSP-related genes to predict the prognosis of patients with cervical cancer (CC) remains elusive. We aimed to delineate the prognosis and biological significance of HSP-related genes in CC. Methods: We collected the transcriptional and clinical data of CC patients from The Cancer Genome Atlas (TCGA) and searched for HSP-related genes in the literature. LASSO and univariate/multivariate Cox regression analyses were utilized to screen genes; 12 genes were found to be related to CC survival, and a prediction model was built. The effectiveness of the model was confirmed using TCGA and GEO, and it was found to be an independent predictor of CC. The nomogram is plotted. The prognostic model was further visualized using calibration curves, which showed good agreement with the predicted outcomes at 1-, 3, and 5 years. Results: We found that low-risk patients had higher immune cell infiltration and stronger immune function, and according to the immunophenoscore and TIDE scores, the low-risk group tended to respond more to immunotherapy. Additionally, we used the GDSC database to predict drug sensitivity in patients with different prognostic risks. Conclusion: In summary, we built a good model to help predict the prognosis of CC patients and provide a reference for personalized treatment and medication for different patients.

The usefulness of CanAssist Breast over Ki67 in breast cancer recurrence risk assessment

BACKGROUND

Assessment of Ki67 by immunohistochemistry (IHC) has limited utility in clinical practice owing to analytical validity issues. According to International Ki67 Working Group (IKWG) guidelines, treatment should be guided by a prognostic test in patients expressing intermediate Ki67 range, >5%-<30%. The objective of the study is to compare the prognostic performance of CanAssist Breast (CAB) with that of Ki67 across various Ki67 prognostic groups.

METHODS

The cohort had 1701 patients. Various risk groups were compared for the distant relapse-free interval (DRFi) derived from Kaplan-Meier survival analysis. As per IKWG, patients are categorized into three risk groups: low-risk (<5%), intermediate risk (>5%-<30%), and high-risk (>30%). CAB generates two risk groups, low and high risk based on a predefined cutoff.

RESULTS

In the total cohort, 76% of the patients were low risk (LR) by CAB as against 46% by Ki67 with a similar DRFi of 94%. In the node-negative sub-cohort, 87% were LR by CAB with a DRFi of 97% against 49% by Ki67 with a DRFi of 96%. In subgroups of patients with T1 or N1 or G2 tumors, Ki67-based risk stratification was not significant while it was significant by CAB. In the intermediate Ki67 (>5%-<30%) category up to 89% (N0 sub-cohort) were LR by CAB and the percentage of LR patients was 25% (p < 0.0001) higher compared to NPI or mAOL. In the low Ki67 (≤5%) group, up to 19% were segregated as high-risk by CAB with 86% DRFi suggesting the requirement of chemotherapy in these low Ki67 patients.

CONCLUSION

CAB provided superior prognostic information in various Ki67 subgroups, especially in the intermediate Ki67 group.

Breast Cancer Patients: Who Would Benefit from Neoadjuvant Chemotherapies?

Neoadjuvant chemotherapy (NACT) was developed with the aims of shrinking tumors or stopping cancer cells from spreading before surgery. Unfortunately, not all breast cancer patients will benefit from NACT, and thus, patients must weigh the risks and benefits of treatment prior to the initiation of therapy. Currently, the data for predicting the efficacy of NACT is limited. Molecular testing, such as Oncotype DX, MammaPrint, and Curebest 95GC, have been developed to assist which breast cancer patients will benefit from the treatment. Patients with an increased level of Human Leukocyte Antigen-DR isotype, tumor-infiltrating lymphocytes, Fizzy-related protein homolog, and a decreased level of tumor-associated macrophages appear to benefit most from NACT.

A retrospective validation of CanAssist Breast in European early-stage breast cancer patient cohort

CanAssist Breast (CAB), a prognostic test uses immunohistochemistry (IHC) approach coupled with artificial intelligence-based machine learning algorithm for prognosis of early-stage hormone-receptor positive, HER2/neu negative breast cancer patients. It was developed and validated in an Indian cohort. Here we report the first blinded validation of CAB in a multi-country European patient cohort. FFPE tumor samples from 864 patients were obtained from-Spain, Italy, Austria, and Germany. IHC was performed on these samples, followed by recurrence risk score prediction. The outcomes were obtained from medical records. The performance of CAB was analyzed by hazard ratios (HR) and Kaplan Meier curves. CAB stratified European cohort (n = 864) into distinct low- and high-risk groups for recurrence (P < 0.0001) with HR of 3.32 (1.85–5.93) like that of mixed (India, USA, and Europe) (n = 1974), 3.43 (2.34–4.93) and Indian cohort (n = 925), 3.09 (1.83–5.21). CAB provided significant prognostic information (P < 0.0001) in women aged ≤ 50 (HR: 4.42 (1.58–12.3), P < 0.0001) and >50 years (HR: 2.93 (1.44–5.96), P = 0.0002). CAB had an HR of 2.57 (1.26–5.26), P = 0.01) in women with N1 disease. CAB stratified significantly higher proportions (77%) as low-risk over IHC4 (55%) (P < 0.0001). Additionally, 82% of IHC4 intermediate-risk patients were stratified as low-risk by CAB. Accurate risk stratification of European patients by CAB coupled with its similar performance inIndian patients shows that CAB is robust and functions independent of ethnic differences. CAB can potentially prevent overtreatment in a greater number of patients compared to IHC4 demonstrating its usefulness for adjuvant systemic therapy planning in European breast cancer patients.

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CanAssist Breast risk (CAB) risk stratification is accurate in European breast cancer patients.

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CAB performance in European cohort was like that of Indian as assessed by low-risk group DMFS, HR and C-index.

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CAB identified significantly higher proportions as low risk compared to IHC4.

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Greater number of IHC4 intermediate risk patients were identified as low risk by CAB.

MPA/DMBA-driven mammary carcinomas

The polycyclic aromatic hydrocarbon 7,12-dimethylbenz[a]anthracene (DMBA, D) administered per os to wild-type female mice bearing slow-release medroxyprogesterone (MPA, M) pellets s.c. drives the formation of mammary carcinomas that recapitulate numerous immunobiological features of human luminal B breast cancer. In particular, M/D-driven mammary carcinomas established in immunocompetent C57BL/6 female mice (1) express hormone receptors, (2) emerge by evading natural immunosurveillance and hence display a scarce immune infiltrate largely polarized toward immunosuppression, (3) exhibit exquisite sensitivity to CDK4/CDK6 inhibitors, and (4) are largely resistant to immunotherapy with immune checkpoint blockers targeting PD-1. Thus, M/D-driven mammary carcinomas evolving in immunocompetent female mice stand out as a privileged preclinical platform for the study of luminal B breast cancer. Here, we provide a detailed protocol for the establishment of M/D-driven mammary carcinomas in wild-type C57BL/6 female mice. This protocol can be easily adapted to generate M/D-driven mammary carcinomas in female mice with most genetic backgrounds (including genetically-engineered mice).