Growth pattern can be used as a new characteristic to predict malignancy in breast cancer

Breast cancer is the most prevalent malignancy in women and the second most common cause of cancer-related death worldwide [1, 2]. The accumulation of cancer cells can be reflected by the spatial shape of the tumor. The formation of a solid mass is the result of constant interactions between proliferating cancer cells and their micro-environment. The cells of solid tumors initiate the process of invasion and metastasis along their spatial growth that can ultimately lead to fatal distant diseases. In women with breast cancer, up to 30% node-negative cases and 70% of node-positive cases will recur [3].

The anatomic TNM classification provides a common language for communicating disease burden. Tumor size is a key criterion for cancer staging and can be used to evaluate the effectiveness of therapies [4]. However, T only describes the largest tumor diameter of the tumor and provides limited description of tumor features despite each tumor having a unique three-dimensional shape. In particular, Wapnir et al. demonstrated that there is a significant overestimation of tumor volume when using the greatest diameter alone for early breast cancer cases [5]. Biological behaviors vary in invasive breast tumors and should not be neglected even though molecular biology is currently widely used in disease staging and prognostic prediction. A larger tumor size, a greater number of metastatic lymph nodes, and distant metastasis represent a later stage. For tumors sharing the same immunophenotype and histologic type, T3 or T4 stage tumors display a rather indolent behavior without rapidly progressing or metastasizing, while some T1 stage tumors have been found to be highly proliferate and metastatic with extremely aggressive behavior. This compels us to investigate whether other tumor features may be associated with tumor behaviors. The morphological growth pattern of tumors is one characteristic that can vary, whereby some tumors display a relative spheroid growth pattern, while others have an ellipsoid growth pattern. Whether the morphological growth pattern can be incorporated with other clinical characteristics is still largely unknown.

In this study, tumors were divided into spheroid and ellipsoid groups based on pathologic length, width and height. We observed a relationship between growth pattern and age, side, primary tumor quadrant, number of lesions, metastatic lymph node number, histologic type, hormone receptor expression, HER-2 expression and treatment. We aimed to investigate whether growth patterns affect tumor features and behaviors and treatment decision making.

In this study, we preliminarily investigated the association between growth patterns and tumor features, tumor behavior and surgery decision making. Our approach provides new insights into tumor features, as we focused on identifying a new way to distinguish breast cancer by dividing growth patterns into spheroids and ellipsoids. The length/height ratio can partially reflect how the masses progressed and help us to infer the possible dynamic nature of the tumor. In particular, we chose postoperative pathologic data (length, width, height, HR status, and HER-2 status) to make our analysis more accurate and reliable. This is because preoperative imaging data have more measurement error when calculating the true size of tumors, and preoperative biopsy samples of a small tumor region may not enable the representative characterization of the tumor as a whole.

Lymph node metastasis acts as a very strong prognostic indicator in breast cancer. In this study, the results showed that an ellipsoid growth pattern has greater potential to cause lymph node metastasis. More metastasis further indicates a worse prognosis. Consistent with our study, Han et al. had shown that tumors with high eccentricity result in worse survival outcomes due to the high incidence of unfavorable prognostic factors, their results also showed that there was a significant association between the degree of eccentricity and the time to distant metastasis in patients with hormone receptor-negative tumors [7]. Our results showed that HR-positive tumors had a more spheroid shape than other subtypes, while the HER-2 status alone had no influence on the growth pattern. This result is in conflict with breast imaging studies that showed triple-negative tumors having more round shapes and smooth margins [8]. We think our finding is more reliable mainly because of two reasons: (1) pathologic data are more accurate than imaging results. (2) There were 176 patients in their study, and the number of patients in their study was small. Therefore, the statistical significance of their data may be insufficient. We also observed that ellipsoid masses are more likely to be located in the central or UOQ of the breast. The reasons for the increase in ellipsoid tumors in the UOQ of the breast remain unknown at this time. This may be due to the development of genetic alterations and more blood supply from axillary in that region. We have also explored the relationship between growth patterns and several closely related breast cancer factors, such as patient age, tumor side, number of lesions and pathologic classification. The lack of meaningful significance prompted us to explore whether the growth pattern has an impact on treatment decision making. Our data showed that the rate of breast-conserving surgery was significantly reduced in patients with ellipsoid masses. Breast-conserving surgery in China often relies on the incision margin of intraoperative frozen pathology. Chinese surgeons prefer to remove a larger area to ensure a clear margin. For ellipsoid tumors, more excised tissue based on length is not conducive to maintain the breast shape, less excised tissue based on height is not conducive to clear margin. Thus, spheroid tumors are more conducive to the extent of resection and margin control. There were 23 patients whose breast masses had already been removed in other small hospitals when they came to these 7 hospitals. Surgical margin was not reported, because small hospitals do not perform intraoperative frozen pathology. They were reluctant to receive further standard breast-conserving surgery due to poor economic conditions or aging. All of the 23 patients’ cancer types were luminal A/B without high-risk factors. Tumors were considered less malignant and can be well controlled by endocrine therapy. Interestingly, all patients who only received mass removal as treatment had spheroid tumors. This phenomenon was also consistent with our data that HR-positive breast cancer cases were more likely to exhibit spheroid growth. We had also tracked the survival status of all patients in our single center. The total number of patients whom we could track with the follow-up was 483. We divided them into four groups according to the molecular subtypes (HR+/HER2−; HR+/HER2+; HR−/HER2+; HR−/HER2−). The survival curves could be seen in supplementary Fig. 2 and 3. The survival analysis also showed that the ellipsoid-like HR+/HER2− and HR−/HER2+ tumors were more likely to have bad RFS and OS.

We believe that the growth pattern of tumors is not random, but determined by the expression of certain genes. It was interesting to notice that increased IL-6 secretion and activation of STAT3 were observed in a Ras-transformed subculture of mammary epithelial cells in 3D cell culure, a phenotype also seen in xenografts and human tumors, but not in standard 2D cultures [9]. Han's team had found that 54 genes were significantly correlated with tumor eccentricity in breast cancer. Among the genes with the highest p value, some genes related to extracellular matrix remodeling such as MMP13 and adamts12 were related to the tumors’ growth pattern [7]. Besides, breast cancer lesions are not homogeneous. Evidence of intratumor heterogeneity has been discovered by chromosomal- and microarray-based comparative genomic hybridization (CGH) and massively parallel sequencing (MPS) analyses [10, 11]. According to the clonal evolution model, intratumoral heterogeneity includes differences in their genetic, phenotypic or behavioral characteristics [10‐12]. In individual breast cancer cases, different subclonal populations of cancer cells may exist across different geographical regions of a tumor (spatial heterogeneity) or evolve over time between the primary tumor and a subsequent local or distant recurrence (temporal heterogeneity) [13, 14]. We hypothesized that different growth patterns may be one of the visible manifestations of genetic heterogeneity. Similar with breast cancer, colorectal tumors which have a laterally spreading pattern show unique expression features of various genes including β-catenin, type IV collagen, and PKC [15]. If highly proliferative clones are located in one marginal area, they are likely to form ellipsoid tumors and cause more metastasis. This finding also supported the idea that a small proportion of cancer cells located at the invading front of solid tumors can determine local invasion and metastasis, while the remaining tumor cells remain nonmetastatic [16].

There are some limitations in our analysis as follows: (i) we did not explore any mechanism regarding why the growth pattern is associated with tumor location, hormone receptor status or number of metastatic lymph nodes. (ii) Although postoperative specimens were used, the tumor size was measured after formalin fixation. Hsu et al. reported that formalin fixation may cause tumor shrinkage and that the measurement after formalin fixation results in an underestimation of actual tumor size [17]. (iii) The complex contour of the malignant mass can be radial and cannot be fully characterized by the dimensional diameter alone. (iv) The concept of TNBC subtypes was first proposed in China in 2019 [18], but our data were obtained from 1999–2008 when the Chinese doctors did not have advanced knowledge of triple negative breast cancer subtypes. The relationship between tumor growth pattern and tumor malignancy in each subtype of TNBC was not included in the analysis. Further study is still necessary to elucidate the mechanism of emergence of different shapes.

In the present study, we performed simple categorization of breast cancer patients based on tumor growth patterns. Our findings indicate that the tumor growth pattern can be a useful indicator to predict tumor malignancy and the prognostic value of breast cancer and that it can contribute to the selection of an optimal therapeutic strategy for individual patients.

The data generated during this study are included in this article. Raw data are available upon reasonable request.