Impact of biomarkers and genetic profiling on breast cancer prognostication: A comparative analysis of the 8th edition of breast cancer staging system

Exploring the Genomic Landscape of Hepatobiliary Cancers to Establish a Novel Molecular Classification System

Taxonomy of hepatobiliary cancer (HBC) categorizes tumors by location or histopathology (tissue of origin, TO). Tumors originating from different TOs can also be grouped by overlapping genomic alterations (GA) into molecular subtypes (MS). The aim of this study was to create novel HBC MSs. Next-generation sequencing (NGS) data from the AACR-GENIE database were used to examine the genomic landscape of HBCs. Machine learning and gene enrichment analysis identified MSs and their oncogenomic pathways. Descriptive statistics were used to compare subtypes and their associations with clinical and molecular variables. Integrative analyses generated three MSs with different oncogenomic pathways independent of TO (n = 324; p < 0.05). HC-1 "hyper-mutated-proliferative state" MS had rapidly dividing cells susceptible to chemotherapy; HC-2 "adaptive stem cell-cellular senescence" MS had epigenomic alterations to evade immune system and treatment-resistant mechanisms; HC-3 "metabolic-stress pathway" MS had metabolic alterations. The discovery of HBC MSs is the initial step in cancer taxonomy evolution and the incorporation of genomic profiling into the TNM system. The goal is the development of a precision oncology machine learning algorithm to guide treatment planning and improve HBC outcomes. Future studies should validate findings of this study, incorporate clinical outcomes, and compare the MS classification to the AJCC 8th staging system.

Classic and New Markers in Diagnostics and Classification of Breast Cancer

Simple Summary

With ever-increasing incidence, breast cancer is considered a most diagnosed type of cancer among women worldwide. Breast cancer arises through malignant transformation of ductal or lobular cells in female (or male) breast and the genetic, phenotypic and morphological heterogeneity has an effect on tumour’s behaviour, thereby instigating a need for individual personalized therapy. A traditional assessment of tumour’s characteristics involves a biopsy and histological analysis of a tumour tissue, and in recent years has been accompanied by analysis of molecular biomarkers to enhance the results. In this work we aimed to thoroughly investigate the latest data in this field of study and give a comprehensive review of novel molecular biomarkers of breast cancer and methodologies used to analyse them.

Abstract

Breast cancer remains the most frequently diagnosed form of female’s cancer, and in recent years it has become the most common cause of cancer death in women worldwide. Like many other tumours, breast cancer is a histologically and biologically heterogeneous disease. In recent years, considerable progress has been made in diagnosis, subtyping, and complex treatment of breast cancer with the aim of providing best suited tumour-specific personalized therapy. Traditional methods for breast cancer diagnosis include mammography, MRI, biopsy and histological analysis of tumour tissue in order to determine classical markers such as estrogen and progesterone receptors (ER, PR), cytokeratins (CK5/6, CK14, C19), proliferation index (Ki67) and human epidermal growth factor type 2 receptor (HER2). In recent years, these methods have been supplemented by modern molecular methodologies such as next-generation sequencing, microRNA, in situ hybridization, and RT-qPCR to identify novel molecular biomarkers. MicroRNAs (miR-10b, miR-125b, miR145, miR-21, miR-155, mir-30, let-7, miR-25-3p), altered DNA methylation and mutations of specific genes (p16, BRCA1, RASSF1A, APC, GSTP1), circular RNA (hsa_circ_0072309, hsa_circRNA_0001785), circulating DNA and tumour cells, altered levels of specific proteins (apolipoprotein C-I), lipids, gene polymorphisms or nanoparticle enhanced imaging, all these are promising diagnostic and prognostic tools to disclose any specific features from the multifaceted nature of breast cancer to prepare best suited individualized therapy.

Expanding the Staging Criteria for T1-2N0 Hormone-Receptor Positive Breast Cancer Patients Enrolled in TAILORx

BACKGROUND

The American Joint Committee on Cancer (AJCC) 8th edition pathologic prognostic staging (PPS) incorporates anatomic and biologic factors. The OncotypeDX Breast Recurrence Score (RS) was included based on the initial report of the TAILORx trial, with T1-2N0 hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer patients who had a RS < 11 staged as PPS 1A. This study examined whether the RS criteria for PPS 1A can be further expanded using patients enrolled in the TAILORx trial.

METHODS

The TAILORx trial enrolled 10,273 HR+HER2- T1-2N0 patients. Those with incomplete HR-status/grade and T3 disease were excluded for analysis. The recurrence-free interval (RFI) was compared between the patients who did and those who did not fall into the current PPS 1A category using the Kaplan-Meier method.

RESULTS

The study enrolled 9535 patients for analysis. The RS was < 11 in 16.1%, 11-17 in 35.9%, 18-25 in 32.4%, and > 25 in 15.6% of the patients. The majority (91.2%) of the patients (including all the T1N0 patients regardless of RS) were PPS 1A, and 8.8% were not-PPS 1A. The median follow-up time was 95 months. The PPS 1A patients had an 8-year RFI of 94.2%, which was similar to that of the patients with a RS of 11-17 who were not-PPS 1A (91.7%; p = 0.07) and better than that of the patients with a RS ≥ 18 who were not-PPS 1A (85.4% for a RS of 18-25, 76.0% for a RS > 25; both p < 0.01). Similar RFI trends were seen in patients who received endocrine therapy or chemotherapy followed by endocrine therapy.

CONCLUSIONS

Patients with T1-2N0 HR+HER2- breast cancer and a RS < 18 have an RFI similar to that of patients staged as PPS 1A by the current AJCC staging system, regardless of treatment, suggesting that the criteria for PPS 1A can be expanded to include a RS < 18.

'I Don't Like Uncertainty, I Like to Know': How and why uveal melanoma patients consent to life expectancy prognostication

BACKGROUND

Technological advances have led to cancer prognostication that is increasingly accurate but often unalterable. However, a reliable prognosis of limited life expectancy can cause psychological distress. People should carefully consider offers of prognostication, but little is known about how and why they decide on prognostication. Using uveal melanoma (UM) patients, we aimed to identify (i) how and why do people with UM decide to accept prognostication and (ii) alignment and divergence of their decision-making from conceptualizations of a 'well-considered' decision.

METHODS

UM provides a paradigm to elucidate clinical and ethical perspectives on prognostication, because prognostication is reliable but prognoses are largely nonameliorable. We used qualitative methods to examine how and why 20 UM people with UM chose prognostication. We compared findings to a template of 'well-considered' decision-making, where 'well-considered' decisions involve consideration of all likely outcomes.

RESULTS

Participants wanted prognostication to reduce future worry about uncertain life expectancy. They spontaneously spoke of hoping for a good prognosis when making their decisions, but largely did not consider the 50% possibility of a poor prognosis. When pressed, they argued that a poor outcome at least brings certainty.

CONCLUSIONS

While respecting decisions as valid expressions of participants' wishes, we are concerned that they did not explicitly consider the realistic possibility of a poor outcome and how this would affect them. Thus, it is difficult to see their decisions as 'well-considered'. We propose that nondirective preference exploration techniques could help people to consider the possibility of a poor outcome.

PATIENT OR PUBLIC CONTRIBUTION

This paper is a direct response to a patient-identified and defined problem that arose in therapeutic and conversational discourse. The research was informed by the responses of patient participants, as we used the material from interviews to dynamically shape the interview guide. Thus, participants' ideas drove the analysis and shaped the interviews to come.

Expanding Criteria for Prognostic Stage IA in Hormone Receptor-Positive Breast Cancer

BACKGROUND

The prognostic significance of patients with low-risk recurrence score (RS) results in the context of the American Joint Committee on Cancer (AJCC) eighth edition pathologic prognostic staging has not been investigated. We evaluated if expanded RS criteria can be considered for downstaging in AJCC pathologic prognostic staging.

METHODS

Using Surveillance, Epidemiology, and End Results data, we identified patients with T1-3N0-3M0 hormone receptor-positive, HER2-negative breast cancer treated from 2010 to 2015 with follow-up data through 2016. We evaluated TNM categories, grade, and RS result. The primary outcome measured was 5-year disease-specific survival (DSS) of patients with low-risk RS results not already pathologic prognostic stage IA, determined by T and N categories per AJCC eighth edition. All statistical tests were 2-sided.

RESULTS

Of 154 050 patients with median follow-up of 49 months (range = 0-83), RS results were obtained in 60 886 (39.5%): RS was less than 11 in 13 570 (22.3%); 11-17 in 22 719 (37.3%); 18-25 in 16 521 (27.1%); and 26 or higher in 8076 (13.3%). Five-year DSS for pathologic prognostic stage IA patients (n = 114 910, 74.6%) was 98.8%. Among N0-1 patients with a RS less than 18 not staged as pathologic prognostic stage IA by current criteria, 5-year DSS was excellent and not statistically significantly different than for pathologic prognostic stage IA patients (97.2%-99.7%; P > .05). For those with a RS of 18-25, there was a small decrease in DSS for T2N0 (2.3%) and modest decrease for T1-2N1 (4.2%-6.4%) compared with pathologic prognostic stage IA patients (P < .001).

CONCLUSION

Patients with a RS less than 18 have excellent 5-year DSS regardless of T category for N0-1 disease suggesting further modification of the AJCC staging system using this cutoff.

Is accurate routine cancer prognostication psychologically harmful? 5-year outcomes of life expectancy prognostication in uveal melanoma survivors

Purpose

Prognostication in cancer is growing in importance as increasingly accurate tools are developed. Prognostic accuracy intensifies ethical concerns that a poor prognosis could be psychologically harmful to survivors. Uveal melanoma (UM) prognostication allows survivors to be reliably told that life expectancy is either normal (good prognosis) or severely curtailed because of metastatic disease (poor prognosis). Treatment cannot change life expectancy. To identify whether prognosis is associated with psychological harm, we compared harm in UM survivors with good and poor prognoses and those who declined testing and compared these outcomes to general population norms.

Methods

Non-randomized 5-year study of a consecutive series of 708 UM survivors (51.6% male, mean age 69.03, SD=12.12) with observations at 6, 12, 24, 36, 48 and 60 months. We operationalized psychological harm as anxiety and depression symptoms, worry about cancer recurrence (WREC) and poor quality of life (QoL).

Results

Compared to other groups, survivors with poor prognoses showed initially elevated anxiety and depression and consistently elevated worry about local or distant recurrence over 5 years. Good prognoses were not associated with outcomes. Generally, no prognostic groups reported anxiety, depression and WREC or QoL scores that exceeded general population norms.

Conclusions

Using a large sample, we found that harm accruing from a poor prognosis was statistically significant over 5 years, but did not exceed general non-cancer population norms.

Implications for Cancer Survivors

Survivors desire prognostic information. At a population level, we do not believe that our findings show sufficiently strong links between prognostication outcome and psychological harm to deny patients the option of knowing their prognosis. Nonetheless, it is important that patients are informed of potential adverse psychological consequences of a poor prognosis.

Validation of the revised 8th AJCC breast cancer clinical prognostic staging system: analysis of 5321 cases from a single institution

The anatomic stage groups (ASG) have been arguably the most powerful in predicting breast cancer (BC) outcomes. Recognizing the prognostic influence of histologic grade and receptor status, the 8th AJCC mandates their incorporation into the newly established prognostic stage groups (PSG). This staging scheme was subsequently revised to provide pathological and clinical prognostic stage tables (PPSG/CPSG) due to its incapability to categorize a significant subset of BCs, with the former only used for patients having surgical resection as the initial treatment, and the latter for all patients. Given the increasingly used neoadjuvant therapy, PPSG cannot be assigned in a significant proportion of higher staged BCs. In this study, we validated the CPSG in a cohort of 5321 BCs. Compared to ASG, the application of CPSG resulted in assigning 16.1% and 27.2% of cases to a higher or a lower stage group in non-stage IV BCs, respectively. The changes were seen mostly frequently in ASG IB, followed by IIIC, IIB, IIA, IIIA, IIIB, and IA. In 7.9% of cases, the assigned CPSG changed more than one stage group from the ASG. CPSG provided an improved overall discriminating power in predicting BC-specific survival when compared to ASG. Pairwise comparison using the Cox proportional hazard model demonstrated further advantages for CPSG as the latter showed a significant difference in all categories when compared to their proximate groups, except IIA vs. IB and IIIA vs. IIIB. In contrast, a significantly different hazard was only seen when comparing IIB vs. IIA, IIIA vs. IIB, and IV vs. IIIC for ASG. Thus, the revised 8th AJCC CPSG provided a superior overall staging scheme for predicting prognostic outcomes in BC patients receiving standard of care treatment. Further validation using the available data with larger populations and longer follow-up may be needed to refine and improve this table.

The use of multi-omics data and approaches in breast cancer immunotherapy: a review

Breast cancer is projected to be the most common cancer in women in 2020 in the USA. Despite high remission rates treatment side effects remain an issue, hence the interest in novel approaches such as immunotherapies which aim to utilize patients' immune systems to target cancer cells. This review summarizes the basics of breast cancer including staging and treatment options, followed by a discussion on immunotherapy, including immune checkpoint blockade. After this, examples of the role of omics-type data and computational biology/bioinformatics in breast cancer are explored. Ultimately, there are several promising areas to investigate such as the prediction of neoantigens and the use of multi-omics data to direct research, with noted appropriate in clinical trial design in terms of end points.

Global Consultation on Cancer Staging: promoting consistent understanding and use

Disease burden is the most important determinant of survival in patients with cancer. This domain, reflected by the cancer stage and codified using the tumour-node-metastasis (TNM) classification, is a fundamental determinant of prognosis. Accurate and consistent tumour classification is required for the development and use of treatment guidelines and to enable clinical research (including clinical trials), cancer surveillance and control. Furthermore, knowledge of the extent and stage of disease is frequently important in the context of translational studies. Attempts to include additional prognostic factors in staging classifications, in order to facilitate a more accurate determination of prognosis, are often made with a lack of knowledge and understanding and are one of the main causes of the inconsistent use of terms and definitions. This effect has resulted in uncertainty and confusion, thus limiting the utility of the TNM classification. In this Position paper, we provide a consensus on the optimal use and terminology for cancer staging that emerged from a consultation process involving representatives of several major international organizations involved in cancer classification. The consultation involved several steps: a focused literature review; a stakeholder survey; and a consultation meeting. This aim of this Position paper is to provide a consensus that should guide the use of staging terminology and secure the classification of anatomical disease extent as a distinct aspect of cancer classification.