Use of biomarkers for breast cancer risk assessment and prevention

Appropriateness and Economic Analysis of Conventional Circulating Biomarkers Assessment in Early Breast Cancer: A Real-World Experience from the E.Pic.A Study

The risk of relapse for early breast cancer (BC) patients persists even after decades and to date, no specific and sensitive effective circulating biomarker for recurrence prediction has been identified yet. The international guidelines do not recommend the assessment of the serum tumor markers CEA and CA15-3 in the follow-up of asymptomatic early BC patients. In our institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) “Dino Amadori”, as part of the E.Pic.A study, which was designed to assess the economic appropriateness of integrated care pathways in early BC, the use of CEA and CA15-3 as circulating tumor biomarkers in early BC patients was evaluated in 1502 patients one year after surgery, from 2015 to 2018, with an overall expense of EUR 51,764. A total of EUR 47,780 (92%) was used for execution of circulating tumor markers in early BC patients with stage 0, I and II tumors, neglecting the current guidelines and considered inappropriate by our professional board. We found that no patients with stage I BC experienced relapse in the 365 days after surgery, and in any case examination of the circulating markers CEA and CA15-3 was considered crucial for diagnosis of relapse. Our findings suggest that this inadequacy is a low-value area, supporting the reallocation of economic resources for interventions of a higher value for patients.

Mammographic density, endocrine therapy and breast cancer risk: a prognostic and predictive biomarker review

BACKGROUND

Endocrine therapy is effective at preventing or treating breast cancer. Some forms of endocrine therapy have been shown to reduce mammographic density. Reduced mammographic density for women receiving endocrine therapy could be used to estimate the chance of breast cancer returning or developing breast cancer in the first instance (a prognostic biomarker). In addition, changes in mammographic density might be able to predict how well a woman responds to endocrine therapy (a predictive biomarker). The role of breast density as a prognostic or predictive biomarker could help improve the management of breast cancer.

OBJECTIVES

To assess the evidence that a reduction in mammographic density following endocrine therapy for breast cancer prevention in women without previous breast cancer, or for treatment in women with early-stage hormone receptor-positive breast cancer, is a prognostic or predictive biomarker.

SEARCH METHODS

We searched the Cochrane Breast Cancer Group Specialised Register, CENTRAL, MEDLINE, Embase, and two trials registers on 3 August 2020 along with reference checking, bibliographic searching, and contact with study authors to obtain further data.

SELECTION CRITERIA

We included randomised, cohort and case-control studies of adult women with or without breast cancer receiving endocrine therapy. Endocrine therapy agents included were selective oestrogen receptor modulators and aromatase inhibitors. We required breast density before start of endocrine therapy and at follow-up. We included studies published in English.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. Two review authors independently extracted data and assessed risk of bias using adapted Quality in Prognostic Studies (QUIPS) and Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tools. We used the GRADE approach to evaluate the certainty of the evidence. We did not perform a quantitative meta-analysis due to substantial heterogeneity across studies.

MAIN RESULTS

Eight studies met our inclusion criteria, of which seven provided data on outcomes listed in the protocol (5786 women). There was substantial heterogeneity across studies in design, sample size (349 to 1066 women), participant characteristics, follow-up (5 to 14 years), and endocrine therapy agent. There were five breast density measures and six density change definitions. All studies had at least one domain as at moderate or high risk of bias. Common concerns were whether the study sample reflected the review target population, and likely post hoc definitions of breast density change. Most studies on prognosis for women receiving endocrine therapy reported a reduced risk associated with breast density reduction. Across endpoints, settings, and agents, risk ratio point estimates (most likely value) were between 0.1 and 1.5, but with substantial uncertainty. There was greatest consistency in the direction and magnitude of the effect for tamoxifen (across endpoints and settings, risk ratio point estimates were between 0.3 and 0.7). The findings are summarised as follows. Prognostic biomarker findings: Treatment Breast cancer mortality Two studies of 823 women on tamoxifen (172 breast cancer deaths) reported risk ratio point estimates of ~0.4 and ~0.5 associated with a density reduction. The certainty of the evidence was low. Recurrence Two studies of 1956 women on tamoxifen reported risk ratio point estimates of ~0.4 and ~0.7 associated with a density reduction. There was risk of bias in methodology for design and analysis of the studies and considerable uncertainty over the size of the effect. One study of 175 women receiving an aromatase inhibitor reported a risk ratio point estimate of ~0.1 associated with a density reduction. There was considerable uncertainty about the effect size and a moderate or high risk of bias in all domains. One study of 284 women receiving exemestane or tamoxifen as part of a randomised controlled trial reported risk ratio point estimates of ~1.5 (loco-regional recurrence) and ~1.3 (distance recurrence) associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the size of the effects. The certainty of the evidence for all recurrence endpoints was very low. Incidence of a secondary primary breast cancer Two studies of 451 women on exemestane, tamoxifen, or unknown endocrine therapy reported risk ratio point estimates of ~0.5 and ~0.6 associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the effect size. The certainty of the evidence was very low. We were unable to find data regarding the remaining nine outcomes prespecified in the review protocol. Prevention Incidence of invasive breast cancer and ductal carcinoma in situ (DCIS) One study of 507 women without breast cancer who were receiving preventive tamoxifen as part of a randomised controlled trial (51 subsequent breast cancers) reported a risk ratio point estimate of ~0.3 associated with a density reduction. The certainty of the evidence was low. Predictive biomarker findings: One study of a subset of 1065 women from a randomised controlled trial assessed how much the effect of endocrine therapy could be explained by breast density declines in those receiving endocrine therapy. This study evaluated the prevention of invasive breast cancer and DCIS. We found some evidence to support the hypothesis, with a risk ratio interaction point estimate ~0.5. However, the 95% confidence interval included unity, and data were based on 51 women with subsequent breast cancer in the tamoxifen group. The certainty of the evidence was low.

AUTHORS' CONCLUSIONS

There is low-/very low-certainty evidence to support the hypothesis that breast density change following endocrine therapy is a prognostic biomarker for treatment or prevention. Studies suggested a potentially large effect size with tamoxifen, but the evidence was limited. There was less evidence that breast density change following tamoxifen preventive therapy is a predictive biomarker than prognostic biomarker. Evidence for breast density change as a prognostic treatment biomarker was stronger for tamoxifen than aromatase inhibitors. There were no studies reporting mammographic density change following endocrine therapy as a predictive biomarker in the treatment setting, nor aromatase inhibitor therapy as a prognostic or predictive biomarker in the preventive setting. Further research is warranted to assess mammographic density as a biomarker for all classes of endocrine therapy and review endpoints.

Expression and prognosis analysis of GINS subunits in human breast cancer

ABSTRACT

GINS subunits, a protein complex composed of GINS1, GINS2, GINS3 and GINS4 in the human genome and the expression level of each GINS subunits plays an important role in different human cancers. As one of the most common malignancies after lung cancer in the world, precise biomarkers for early diagnosis and treatment in breast cancer are important. The purpose of our study was to elucidate the expression and prognostic value of GINS subunits in breast cancer.The purpose of present study was to explore the expression level of GINS subunits in breast cancer patients.In the present study, we investigated the gene alteration, gene expression and potential prognostic value of GINS subunits by using the Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, cBioPortal, and bc-GenExMiner databases. Then, the GeneMANIA database was used to show the genes that associated with GINS subunits. Furthermore, gene ontology pathway analysis was conducted by using the Metascape database. Finally, immune infiltration analysis in GINS subunits were evaluated using the Tumor Immune Estimation Resource (TIMER) database.Our analyses demonstrated that the expression levels of different GINS subunits were different between breast cancer and normal breast tissues. The expression levels of GINS1, GINS2, and GINS4 were significantly higher in breast cancer tissues than in normal tissues. Survival analysis revealed that increased the expression levels of GINS subunits were associated with poor prognoses in all patients with breast cancer. Gene ontology pathway enrichment analysis of the GINS subunits suggested that GINS subunits involved in pathways including the cell cycle checkpoint, DNA replication and other meaningful signaling pathways.We systemically analyzed the expression, prognostic, clinicopathologic values, and potential functional networks of GINS subunits in breast cancer. Our findings showed that individual GINS subunits could be new potential prognostic biomarkers for breast cancer. However, further verification studies are still needed to prove the clinical value of GINS subunits in breast cancer patients.

Exemestane Use in Postmenopausal Women at High Risk for Invasive Breast Cancer: Evaluating Biomarkers of Efficacy and Safety

This phase II trial evaluated clinical markers of efficacy and safety of exemestane in postmenopausal women at increased risk for breast cancer. Postmenopausal women (n = 42) at risk for invasive breast cancer received 25 mg exemestane daily for 2 years along with calcium and vitamin D. The primary outcome was change in mammographic density (MD) after one year. Secondary outcomes included change in serum steroid hormones as well as change in trefoil protein 1 (TFF1) and proliferating cell nuclear antigen (PCNA) in breast tissue. Safety and tolerability were also assessed. MD decreased at 1 year and was significant at 2 years [mean change = -4.1%; 95% confidence intervals (CI), -7.2 to -1.1; P = 0.009]. Serum estradiol and testosterone levels significantly decreased at 3 months and remained suppressed at 12 months. After 1 year of treatment, TFF1 intensity decreased (mean change -1.32; 95% CI, -1.87 to -0.76; P < 0.001). Exemestane was safe and well tolerated. Exemestane decreased MD and expression of breast tissue TFF1. It was well tolerated with few clinically relevant side effects. MD and breast tissue TFF1 are potential biomarkers of breast cancer-preventive effects of exemestane in high-risk postmenopausal women.

Breast cancer prevention across the cancer care continuum

OBJECTIVES

To review the current state of breast cancer prevention from primary prevention through survivorship, highlight cross-cutting issues, and discuss strategies for clinical integration and future research.

DATA SOURCES

Published articles between 1985 and 2015 and original research.

CONCLUSION

Cancer risk persists across the lifespan. Interprofessional strategies to reduce morbidity and mortality from cancer include primary, secondary, and tertiary prevention (survivorship). Prevention strategies across the cancer care continuum are cross-cutting and focus on measures to: prevent the onset of disease, identify and treat asymptomatic persons who have already developed risk factors or preclinical disease, and restore function, minimize the negative effects of disease, and prevent disease-related complications.

IMPLICATIONS FOR NURSING PRACTICE

Oncology nurses and advanced practice nurses are vital in the delivery of breast cancer prevention strategies.

Concordant effects of aromatase inhibitors on gene expression in ER+ Rat and human mammary cancers and modulation of the proteins coded by these genes

Aromatase inhibitors are effective in therapy/prevention of estrogen receptor-positive (ER⁺) breast cancers. Rats bearing methylnitrosourea (MNU)-induced ER⁺ mammary cancers were treated with the aromatase inhibitor vorozole (1.25 mg/kg BW/day) for five days. RNA expression showed 162 downregulated and 180 upregulated (P < 0.05 and fold change >1.5) genes. Genes modulated by vorozole were compared with published data from four clinical neoadjuvant trials using aromatase inhibitors (anastrozole or letrozole). More than 30 genes and multiple pathways exhibited synchronous changes in animal and human datasets. Cell-cycle genes related to chromosome condensation in prometaphase [anaphase-prometaphase complex (APC) pathway, including Aurora-A kinase, BUBR1B, TOP2, cyclin A, cyclin B CDC2, and TPX-2)] were downregulated in animal and human studies reflecting the strong antiproliferative effects of aromatase inhibitors. Comparisons of rat arrays with a cell culture study where estrogen was removed from MCF-7 cells showed decreased expression of E2F1-modulated genes as a major altered pathway. Alterations of the cell cycle and E2F-related genes were confirmed in a large independent set of human samples (81 pairs baseline and two weeks anastrozole treatment). Decreases in proliferation-related genes were confirmed at the protein level for cyclin A2, BuRB1, cdc2, Pttg, and TPX-2. Interestingly, the proteins downregulated in tumors were similarly downregulated in vorozole-treated normal rat mammary epithelium. Finally, decreased expression of known estrogen-responsive genes (including TFF, 1,3, progesterone receptor, etc.) were decreased in the animal model. These studies demonstrate that gene expression changes (pathways and individual genes) are similar in humans and the rat model.

Serum factors and clinical characteristics associated with serum E-screen activity

BACKGROUND

The E-Screen bioassay can measure the mitogenicity of human serum and thus may be useful as a biomarker in epidemiologic studies of breast cancer. While the assay's MCF-7 cells are known to proliferate in response to estrogen, the specific determinants of variation in E-Screen activity in human serum samples are poorly understood. We sought to identify serum molecules and patient characteristics associated with serum E-Screen activity among postmenopausal women.

METHODS

Postmenopausal women (N = 219) aged 55 to 70 years with no history of postmenopausal hormone use or breast cancer completed a questionnaire and provided a blood sample. Serum was analyzed for E-Screen activity and a variety of molecules including sex hormones, growth factors, and environmental chemicals. Stepwise selection procedures were used to identify correlates of E-Screen activity.

RESULTS

Serum samples from all women had detectable E-Screen activity, with a median estradiol equivalents value of 0.027 ng/mL and interquartile range of 0.018-0.036 ng/mL. In the final multivariable-adjusted model, serum E-Screen activity was positively associated with serum estradiol, estrone, insulin-like growth factor-binding protein (IGFBP)-3, and testosterone levels (all P < 0.05), as well as body mass index (P = 0.03). Serum E-Screen activity was lower among women with higher SHBG (P < 0.0001) and progesterone levels (P = 0.03).

CONCLUSION

Serum E-Screen activity varies according to levels of endogenous estrogens and other serum molecules. Obesity appears to confer additional serum mitogenicity beyond its impact on the measured hormones and growth factors.

IMPACT

By capturing mitogenicity due to a variety of patient and serum factors, the E-Screen may provide advantages for use as a biomarker in breast cancer studies.

Assessment of RNA in human breast tissue sampled by random periareolar fine needle aspiration and ductal lavage and processed as fixed or frozen specimens

Ductal lavage (DL) and random periareolar fine needle aspiration (RPFNA) have both been proposed as minimally invasive techniques to sample breast tissue during breast cancer prevention trials. Laser capture microdissection (LCM), linear RNA amplification and quantitative real-time polymerase chain reaction (qPCR) theoretically overcome the limitations of small specimen size obtained with DL and RPFNA. In order to test the yield, relative stability and amplifiability of RNA from fixed and archived RPFNA and DL specimens, breast tissue was sampled from individual high risk women (n=9) by both DL and RPFNA. RPFNA samples showed good RNA/cDNA yield and amplification while only 2 of 9 of the paired DL specimens had cDNA of adequate quality for subsequent PCR. One and two rounds of linear amplification provided approximately a 200- and 20,000-fold enrichment of RNA, respectively. PCR analysis consistently detected ER and COX-1 mRNA in the majority of RPFNA samples examined while pS2, PCNA, VEGF and survivin expression varied with subject. RNA yield and/or stability was greater for fixed and archived RPFNA than DL specimens of breast tissue. In a subsequent study examining an expanded biomarker gene panel in fixed vs. frozen RPFNA samples, mRNA profiles and ranked relative mRNA abundance were similar (r=0.89) for frozen and fixed RPFNA specimens. In summary, frozen RPFNA samples may be optimal for RNA endpoints in human breast cancer prevention trials but fixed RPFNA specimens allow similar analyses with greater convenience.

A case for combined ovarian and breast cancer prevention

Targeted prevention of ovarian cancer is hindered by the inaccessibility of ovarian tissue, lack of accepted biomarkers and low disease incidence. However, ovarian cancer has common risk factors and shared etiologies with breast cancer. Chemoprevention of ovarian cancer has been demonstrated incidentally during testing of novel breast cancer prevention drugs. Here it is hypothesized that the development of combined ovarian and breast cancer prevention strategies is a preferable strategy for ovarian cancer prevention.

Mammographic density and risk of breast cancer by adiposity: an analysis of four case-control studies

The association of mammographic breast density with breast cancer risk may vary by adiposity. To examine effect modification by body mass index (BMI), the authors standardized mammographic density data from four case-control studies (1994-2002) conducted in California, Hawaii and Minnesota and Gifu, Japan. The 1,699 cases and 2,422 controls included 45% Caucasians, 40% Asians and 9% African-Americans. Using ethnic-specific BMI cut points, 34% were classified as overweight and 19% as obese. A single reader assessed density from mammographic images using a computer-assisted method. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) while adjusting for potential confounders. Modest heterogeneity in the relation between percent density and breast cancer risk across studies was observed (p(heterogeneity) = 0.08). Cases had a greater age-adjusted mean percent density than controls: 31.7% versus 28.5%, respectively (p <0.001). Relative to <20 percent density, the ORs for >35 were similar across BMI groups whereas the OR for 20-35 was slightly higher in overweight (OR = 1.69, 95% CI: 1.28, 2.24) and obese (OR = 1.62, 95% CI: 1.12, 2.33) than in normal weight women (OR = 1.49, 95% CI: 1.11, 2.01). Furthermore, limited evidence of effect modification by BMI of the OR per 10% increase in percent density (p(interaction) = 0.06) was observed, including subgroup analyses by menopausal status and in analyses that excluded women at the extremes of the BMI scale. Our findings indicate little, if any, modification by BMI of the effects of breast density on breast cancer risk.

Biomarkers for early detection and as surrogate endpoints in cancer prevention trials: issues and opportunities

In order to improve the early detection and diagnosis of cancer, give more accurate prognoses, stratify individuals by risk, predict response to treatment, and help the transition of basic research into clinical application, biomarkers are needed that accurately represent or predict clinical outcomes. To be useful in trials for chemopreventive agent development, biomarkers must be subject to modulation, easy to obtain and quantify, and have biological meaning, ideally representing steps in well-understood carcinogenic pathways. Though difficult to validate fully, wisely chosen biomarkers in early-phase trials can inform the prioritization of large-scale, long-term trials that measure clinical outcomes. When well-designed, smaller trials using biomarkers as surrogate endpoints should promote faster decisions regarding which targeted preventive agents to pursue, promising greater progress in the personalization of medicine. Biomarkers could become useful in distinguishing indolent from aggressive forms of ductal carcinoma in situ as well as localized invasive breast and prostate cancer, lesions that are often overtreated. Chemopreventive strategies that reduce the progression of early forms of premalignancy can benefit patients not only by reducing their risk of cancer and death from cancer but also by reducing their need for invasive interventions. Genomic and proteomic methods offer the possibility of revealing new potential markers, especially for diseases whose biology is complex or not well understood. Panels of markers may be used to accommodate the molecular heterogeneity of cancers. Biomarkers in phase 2 prevention trials of combinations of chemopreventive drugs have been used to demonstrate synergistic action of multiple agents, allowing use of lower doses, with less toxicity, a critical feature of interventions intended for cancer prevention.

Molecular markers for early detection

A common belief is that the earlier that cancer is detected, the better the chance exists for reduced mortality and morbidity. The advent of new and emerging molecular, genetic, and imaging technologies has broadened the possible strategies for early detection and prevention, but a beneficial impact on mortality needs to be supported by clinical evidence. Molecular markers are being identified that are enhancing our ability to predict and detect cancer before it develops and at the earliest signs of impending carcinogenic transformation. Of the innumerable molecular markers in development, a standalone early detection marker with acceptable sensitivity and specificity is available for bladder cancer, although for most cancer sites there are promising avenues of research that will likely produce results in the next decade. The perfect molecular marker would be one that is inherently related to the disease, specifically to the processes of malignant tumorigenesis or to the defense mechanisms of the individual. For example, mutations associated with increased cancer risk often produce gene products that interfere with tumor-suppressor pathways (eg, DNA repair or cell-cycle control) or support oncogenic pathways (eg, through genetic instability or silencing the apoptotic pathway). Finding molecular markers associated with these processes, and where in the process they produce their actions, can lead to interventions based on maintaining support for the normal process and interrupting the action of the products of the mutation. The search for molecular markers for cancer prevention and early detection presents a formidable challenge that requires a systematic and scientifically sound validation process. The search encompasses a broad range of scientific disciplines, including biochemistry, genetics, histology, immunology, informatic technologies, and epidemiology; strategies to identify and understand molecular markers are approached with multidisciplinary teams focused on understanding the mechanistic basis of cancer and the processes and pathways that underlie carcinogenesis.