Histological grade concordance between diagnostic core biopsy and corresponding surgical specimen in HR-positive/HER2-negative breast carcinoma

Pathological Changes Following Neoadjuvant Endocrine Therapy (NAET): A Multicentre Study of 391 Breast Cancers

Oestrogen receptor (ER)-positive breast cancer (BC) is generally well responsive to endocrine therapy. Neoadjuvant endocrine therapy (NAET) is increasingly being used for downstaging ER-positive tumours. This study aims to analyse the effect of NAET on a well-characterised cohort of ER-positive BC with particular emphasis on receptor expression. This is a retrospective United Kingdom (UK) multicentre study of 391 patients who received NAET between October 2012 and October 2020. Detailed analyses of the paired pre- and post-NAET morphological changes and hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression were performed. The median duration of NAET was 86 days, with median survival and overall survival rates of 380 days and 93.4%, respectively. A total of 90.3% of cases achieved a pathological partial response, with a significantly higher rate of response in the HER2-low cancers. Following NAET, BC displayed some pathological changes involving the tumour stroma including central scarring and an increase in tumour infiltrating lymphocytes (TILs) and tumour cell morphology. Significant changes associated with the duration of NAET were observed in tumour grade (30.6% of cases), with downgrading identified in 19.3% of tumours (p < 0.001). The conversion of ER status from positive to low or negative was insignificant. The conversion of progesterone receptor (PR) and HER2 status to negative status was observed in 31.3% and 38.1% of cases, respectively (p < 0.001). HER2-low breast cancer decreased from 63% to 37% following NAET in the paired samples. Significant morphological and biomarker changes involving PR and HER2 expression occurred following NAET. The findings support biomarker testing on pre-treatment core biopsies and post-treatment residual carcinoma.

Expression, assessment and significance of Ki67 expression in breast cancer: an update

Ki67 expression is one of the most important and cost-effective surrogate markers to assess for tumour cell proliferation in breast cancer (BC). The Ki67 labelling index has prognostic and predictive value in patients with early-stage BC, particularly in the hormone receptor-positive, HER2 (human epidermal growth factor receptor 2)-negative (luminal) tumours. However, many challenges exist in using Ki67 in routine clinical practice and it is still not universally used in the clinical setting. Addressing these challenges can potentially improve the clinical utility of Ki67 in BC. In this article, we review the function, immunohistochemical (IHC) expression, methods for scoring and interpretation of results as well as address several challenges of Ki67 assessment in BC. The prodigious attention associated with use of Ki67 IHC as a prognostic marker in BC resulted in high expectation and overestimation of its performance. However, the realisation of some pitfalls and disadvantages, which are expected with any similar markers, resulted in an increasing criticism of its clinical use. It is time to consider a pragmatic approach and weigh the benefits against the weaknesses and identify factors to achieve the best clinical utility. Here we highlight the strengths of its performance and provide some insights to overcome the existing challenges.

High concordance of 70-gene recurrence risk signature and 80-gene molecular subtyping signature between core needle biopsy and surgical resection specimens in early-stage breast cancer

BACKGROUND AND OBJECTIVES

With increased neoadjuvant therapy recommendations for early-stage breast cancer patients due to the COVID-19 pandemic, it is imperative that molecular diagnostic assays provide reliable results from preoperative core needle biopsies (CNB). The study objective was to determine the concordance of MammaPrint and BluePrint results between matched CNB and surgical resection (SR) specimens.

METHODS

Matched tumor specimens (n = 121) were prospectively collected from women enrolled in the FLEX trial (NCT03053193). Concordance is reported using overall percentage agreement and Cohen's kappa coefficient. Correlation is reported using Pearson correlation coefficient.

RESULTS

We found good concordance for MammaPrint results between matched tumor samples (90.9%, κ = 0.817), and a very strong correlation of MammaPrint indices (r = 0.94). The concordance of BluePrint subtyping in matched samples was also excellent (98.3%).

CONCLUSIONS

CNB samples demonstrated high concordance with paired SR samples for MammaPrint risk classification and BluePrint molecular subtyping, suggesting that physicians are provided with accurate prognostic information that can be used to guide therapy decisions.

What do cellular responses to acidity tell us about cancer?

The notion that invasive cancer is a product of somatic evolution is a well-established theory that can be modelled mathematically and demonstrated empirically from therapeutic responses. Somatic evolution is by no means deterministic, and ample opportunities exist to steer its trajectory towards cancer cell extinction. One such strategy is to alter the chemical microenvironment shared between host and cancer cells in a way that no longer favours the latter. Ever since the first description of the Warburg effect, acidosis has been recognised as a key chemical signature of the tumour microenvironment. Recent findings have suggested that responses to acidosis, arising through a process of selection and adaptation, give cancer cells a competitive advantage over the host. A surge of research efforts has attempted to understand the basis of this advantage and seek ways of exploiting it therapeutically. Here, we review key findings and place these in the context of a mathematical framework. Looking ahead, we highlight areas relating to cellular adaptation, selection, and heterogeneity that merit more research efforts in order to close in on the goal of exploiting tumour acidity in future therapies.

Cancer Grade Model: a multi-gene machine learning-based risk classification for improving prognosis in breast cancer

BACKGROUND

Prognostic stratification of breast cancers remains a challenge to improve clinical decision making. We employ machine learning on breast cancer transcriptomics from multiple studies to link the expression of specific genes to histological grade and classify tumours into a more or less aggressive prognostic type.

MATERIALS AND METHODS

Microarray data of 5031 untreated breast tumours spanning 33 published datasets and corresponding clinical data were integrated. A machine learning model based on gradient boosted trees was trained on histological grade-1 and grade-3 samples. The resulting predictive model (Cancer Grade Model, CGM) was applied on samples of grade-2 and unknown-grade (3029) for prognostic risk classification.

RESULTS

A 70-gene signature for assessing clinical risk was identified and was shown to be 90% accurate when tested on known histological-grade samples. The predictive framework was validated through survival analysis and showed robust prognostic performance. CGM was cross-referenced with existing genomic tests and demonstrated the competitive predictive power of tumour risk.

CONCLUSIONS

CGM is able to classify tumours into better-defined prognostic categories without employing information on tumour size, stage, or subgroups. The model offers means to improve prognosis and support the clinical decision and precision treatments, thereby potentially contributing to preventing underdiagnosis of high-risk tumours and minimising over-treatment of low-risk disease.

Molecular characterization of breast cancer needle core biopsy specimens by the 21-gene Breast Recurrence Score test

BACKGROUND AND OBJECTIVE

Recent COVID-19 pandemic guidelines recommend genomic assessment of core biopsies to help guide treatment decisions in estrogen receptor (ER)-positive early-stage breast cancer. Herein we characterize biopsy and excisional breast cancer specimens submitted for 21-gene testing.

METHODS

US samples submitted to Genomic Health for 21-gene testing (01/2004-04/2020) were assessed by pathologists and analyzed by a standardized quantitative reverse transcription-polymerase chain reaction. Predefined cutoffs were: ESR1 (positive ≥6.5), PGR (positive ≥5.5), and ERBB2 (negative <10.7). ER status by immunohistochemistry (IHC) and lymph node status were determined locally. Median and interquartile range were reported for continuous variables, and total and percent for categorical variables. Distributions were assessed overall, by age, and by nodal involvement.

RESULTS

Of 919 701 samples analyzed, 13% were biopsies and 87% were excisions. Initial assay success rates were 94.5% (biopsies) and 97.3% (excisions). ER IHC concordance with central ESR1 was 96.8% (biopsies) and 97.6% (excisions). Biopsy and excisional medians were: Recurrence Score results 16 (each); ESR1 10.2 (each); PGR 7.7 and 7.6; ERBB2 9.4 and 9.2, respectively.

CONCLUSIONS

Biopsy submissions for 21-gene testing are common and consistently generate results that are very similar to the experience with excisions. The 21-gene test can be performed reliably on core biopsies.

Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high-resolution magic angle spinning 1 H NMR spectroscopy

High-resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi-core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9- and 1.3-ppm signals) and metabolite quantification using HR MAS ¹ H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16-0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one-way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue.

[Histological grading of breast cancer]

From a historical perspective, histological grading was the earliest cell-based method for assessing tumor biology and the prognosis of breast cancer. This review article provides detailed and practical instructions for grading of breast cancer in routine diagnostics. Furthermore, the increasing relevance of precise histological grading in the era of molecular pathology is discussed.

Reliability of the Ki67-Labelling Index in Core Needle Biopsies of Luminal Breast Cancers is Unaffected by Biopsy Volume

BACKGROUND

Assessing prognostic and predictive factors like the Ki67 labelling index (Ki67-LI) in breast cancer core needle biopsies (CNB) may be hampered by undersampling. Our aim was to arrive at a representative assessment of Ki67-LI in CNB of luminal breast cancers by defining optimal cutoffs and establishing the minimum CNB volume needed for highest concordance of Ki67-LI between CNB and subsequent surgical excision biopsy (SEB).

METHODS

We assessed the Ki67-LI in CNB and subsequent SEB of 170 luminal breast cancers according to two counting methods recommended by the International Ki67 in Breast Cancer Working Group and applied the cutoffs to distinguish low and high proliferation given by the St Gallen 2013 and 2015 consensus, respectively. We then compared CNB volume characteristics for cases with concordant and discordant Ki67-LI between CNB versus SEB.

RESULTS

Highest concordance (75%, κ = 0.44) between CNB and SEB was achieved using the method that assesses the average tumor Ki67-LI and a cutoff of 20%. No significant differences were found between cases with concordant and discordant Ki67-LI in CNB versus SEB for number of biopsy cores, total core length, tumor tissue length, or total CNB or tumor tissue area size in the CNB for two various cutoffs.

CONCLUSIONS

A concordance of 75% between CNB and SEB can be achieved for the Ki67-LI using a method assessing average Ki67-LI at the threshold of 20%. Increasing CNB volume did not result in improved agreement rates, indicating that reliability of Ki67 levels in CNB of luminal breast cancers is unaffected by CNB volume.

The reliability of histological grade in breast cancer core needle biopsies depends on biopsy size: a comparative study with subsequent surgical excisions

AIMS

In breast cancer patients undergoing neoadjuvant chemotherapy, histological grading needs to be performed on core needle biopsies (CNBs) that may not be representative of the whole tumour when they are small. Our aim was to study the influence of biopsy size on agreement rates for histological grade between CNBs and subsequent surgical excision biopsies (SEBs).

METHODS AND RESULTS

We calculated agreement and Cohen's κ between CNBs and SEBs of 300 early-stage breast cancers. The number of cores, total core length, total tumour length and tumour/tissue ratio were assessed for each CNB set. Agreement rates for grade were calculated for different classes of core number and tumour/tissue ratio, and for total core lengths and tumour lengths per CNB set in 5-15-mm intervals. Agreement on grade between CNBs and SEBs was 73% (κ = 0.59), with underestimation of grade in CNBs in 26% of cases and overestimation in 1% of cases. There was significantly higher concordance between CNBs and SEBs at a total core length of ≥50 mm than at a total core length of <50 mm (83% versus 68% agreement, P = 0.007), at a tumour length of ≥15 mm than at tumour length of <15 mm in CNBs (79% versus 67% agreement, P = 0.036), and at three or more cores than at fewer than three cores (75% versus 58% agreement, P = 0.048). The tumour/tissue ratio, pathological tumour size and radiological tumour size were not statistically different between concordant and discordant cases.

CONCLUSIONS

Agreement rates for histological grade in CNBs versus SEBs improve with increasing biopsy sample size.

Meta-analysis of the concordance of histological grade of breast cancer between core needle biopsy and surgical excision specimen

BACKGROUND

With the increasing use of neoadjuvant chemotherapy and minimally invasive ablative therapy in breast cancer, pretreatment assessment of tumour grade on core needle biopsy (CNB) is increasingly needed. However, grading on CNB is possibly less accurate than grading based on the surgical excision specimen. A systematic review and meta-analysis of the literature was conducted to derive a reliable estimate of the agreement in tumour grading between CNB and subsequent surgical excision.

METHODS

Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) criteria, Embase, PubMed and the Cochrane Library were searched. Pooled proportions of agreement in grading between CNB and the excision specimen, Cohen's κ and percentages of overestimation and underestimation were calculated. Random-effects models were applied because of substantial heterogeneity, assessed by I² test. Determinants of the level of agreement in grading were explored with meta-regression.

RESULTS

Thirty-four articles were included in the systematic review (6029 patients) and 33 in the meta-analysis (4980 patients). Pooled agreement and κ were 71·1 (95 per cent c.i. 68·8 to 73·3) per cent and 0·54 (0·50 to 0·58) respectively. Underestimation and overestimation occurred in 19·1 (17·1 to 21·3) and 9·3 (7·7 to 11·4) per cent respectively. Meta-regression showed associations between agreement of histological type (positive association) and proportion of patients with oestrogen receptor-positive disease (negative association) and grade agreement.

CONCLUSION

Grading on CNB corresponds moderately with grading based on excision specimens, with underestimation in about one in five patients. Incorrect CNB tumour grading has limited clinical implications, as multiple factors influence decision-making for adjuvant systemic therapy.

Correlation between conductivity and prognostic factors in invasive breast cancer using magnetic resonance electric properties tomography (MREPT)

PURPOSE

To investigate the correlation between conductivity and prognostic factors of invasive breast cancer using magnetic resonance electric properties tomography (MREPT).

METHODS

This retrospective study was approved by the Institutional Review Board, and verbal informed consent was obtained prior to breast MRI. This study included 65 women with surgically confirmed invasive breast cancers measuring 1 cm or larger on T2-weighted fast spin echo (FSE). Phase-based MREPT and the coil combination technique were used to reconstruct conductivity. Simple and multiple linear regression analysis were used to find an independent factor associated with conductivity.

RESULTS

In total tumours, tumours with HER-2 overexpression showed lower conductivity than those without, and HER-2 overexpression was independently associated with conductivity. In 37 tumours 2 cm or larger, tumours with high mitosis or PR positivity showed higher conductivity than those without, and high mitosis and PR positivity were independently associated with conductivity. In 28 tumours 1-2 cm in size, there were no differences in conductivity according to the prognostic factors.

CONCLUSION

Conductivity values measured using MREPT are associated with the HER-2 overexpression status, and may provide information about mitosis and the PR status of invasive breast cancers 2 cm or larger.

KEY POINTS

• In all tumours, HER-2 overexpression was independently associated with conductivity. • In tumours ≥ 2 cm, high mitosis and PR positivity were associated with conductivity. • Conductivity is associated with the HER-2 overexpression status of invasive breast cancers.

Response to dual HER2 blockade in a patient with HER3-mutant metastatic breast cancer

BACKGROUND

HER3 activating mutations have been shown in preclinical models to be oncogenic and ligand-independent, but to depend on kinase-active HER2.

PATIENTS AND METHODS

Whole-exome sequencing of the primary HER2-negative breast cancer and its HER2-negative synchronous liver metastasis from a 46-year-old female revealed the presence of an activating and clonal HER3 G284R mutation.

RESULTS

HER2 dual blockade with trastuzumab and lapatinib as third-line therapy led to complete metabolic response in 2 weeks and confirmed radiological partial response after 8 weeks. Following the resection of the liver metastasis, the patient remains disease-free 40 weeks after initiation of the HER2 dual blockade therapy. Immunohistochemical analysis demonstrated a substantial reduction of phospho-rpS6 and phospho-AKT in the post-therapy biopsy of the liver metastasis.

DISCUSSION

This is the first-in-man evidence that anti-HER2 therapies are likely effective in breast cancers harboring HER3 activating mutations.