Bimodal age distribution at diagnosis in breast cancer persists across molecular and genomic classifications

The Cancer Spectrum Theory

SUMMARY

Biological characteristics of tumors are heterogeneous, forming spectra in terms of several factors such as age at onset, anatomic spatial localization, tumor subtyping, and the degree of tumor aggressiveness (encompassing a neoplastic property spectrum). Instead of blindly using dichotomized approaches, the application of the multicategorical and continuous analysis approaches to detailed cancer spectrum data can contribute to a better understanding of the etiology of cancer, ultimately leading to effective prevention and precision oncology. We provide examples of cancer spectra and emphasize the importance of integrating the cancer spectrum theory into large-scale population cancer research.

Host, reproductive, and lifestyle factors in relation to quantitative histologic metrics of the normal breast

BACKGROUND

Emerging data indicate that variations in quantitative epithelial and stromal tissue composition and their relative abundance in benign breast biopsies independently impact risk of future invasive breast cancer. To gain further insights into breast cancer etiopathogenesis, we investigated associations between epidemiological factors and quantitative tissue composition metrics of the normal breast.

METHODS

The study participants were 4108 healthy women ages 18-75 years who voluntarily donated breast tissue to the US-based Susan G. Komen Tissue Bank (KTB; 2008-2019). Using high-accuracy machine learning algorithms, we quantified the percentage of epithelial, stromal, adipose, and fibroglandular tissue, as well as the proportion of fibroglandular tissue that is epithelium relative to stroma (i.e., epithelium-to-stroma proportion, ESP) on digitized hematoxylin and eosin (H&E)-stained normal breast biopsy specimens. Data on epidemiological factors were obtained from participants using a detailed questionnaire administered at the time of tissue donation. Associations between epidemiological factors and square root transformed tissue metrics were investigated using multivariable linear regression models.

RESULTS

With increasing age, the amount of stromal, epithelial, and fibroglandular tissue declined and adipose tissue increased, while that of ESP demonstrated a bimodal pattern. Several epidemiological factors were associated with individual tissue composition metrics, impacting ESP as a result. Compared with premenopausal women, postmenopausal women had lower ESP [β (95% Confidence Interval (CI)) = -0.28 (- 0.43, - 0.13); P < 0.001] with ESP peaks at 30-40 years and 60-70 years among pre- and postmenopausal women, respectively. Pregnancy [β (95%CI) vs nulligravid = 0.19 (0.08, 0.30); P < 0.001] and increasing number of live births (P-trend < 0.001) were positively associated with ESP, while breastfeeding was inversely associated with ESP [β (95%CI) vs no breastfeeding = -0.15 (- 0.29, - 0.01); P = 0.036]. A positive family history of breast cancer (FHBC) [β (95%CI) vs no FHBC = 0.14 (0.02-0.26); P = 0.02], being overweight or obese [β (95%CI) vs normal weight = 0.18 (0.06-0.30); P = 0.004 and 0.32 (0.21-0.44); P < 0.001, respectively], and Black race [β (95%CI) vs White = 0.12 (- 0.005, 0.25); P = 0.06] were positively associated with ESP.

CONCLUSION

Our findings revealed that cumulative exposure to etiological factors over the lifespan impacts normal breast tissue composition metrics, individually or jointly, to alter their dynamic equilibrium, with potential implications for breast cancer susceptibility and tumor etiologic heterogeneity.

Deep Transcriptome Profiling of Multiple Myeloma Using Quantitative Phenotypes

BACKGROUND

Transcriptome studies are gaining momentum in genomic epidemiology, and the need to incorporate these data in multivariable models alongside other risk factors brings demands for new approaches.

METHODS

Here we describe SPECTRA, an approach to derive quantitative variables that capture the intrinsic variation in gene expression of a tissue type. We applied the SPECTRA approach to bulk RNA sequencing from malignant cells (CD138+) in patients from the Multiple Myeloma Research Foundation CoMMpass study.

RESULTS

A set of 39 spectra variables were derived to represent multiple myeloma cells. We used these variables in predictive modeling to determine spectra-based risk scores for overall survival, progression-free survival, and time to treatment failure. Risk scores added predictive value beyond known clinical and expression risk factors and replicated in an external dataset. Spectrum variable S5, a significant predictor for all three outcomes, showed pre-ranked gene set enrichment for the unfolded protein response, a mechanism targeted by proteasome inhibitors which are a common first line agent in multiple myeloma treatment. We further used the 39 spectra variables in descriptive modeling, with significant associations found with tumor cytogenetics, race, gender, and age at diagnosis; factors known to influence multiple myeloma incidence or progression.

CONCLUSIONS

Quantitative variables from the SPECTRA approach can predict clinical outcomes in multiple myeloma and provide a new avenue for insight into tumor differences by demographic groups.

IMPACT

The SPECTRA approach provides a set of quantitative phenotypes that deeply profile a tissue and allows for more comprehensive modeling of gene expression with other risk factors.

Characteristics of female breast cancer in japan: annual report of the National Clinical Database in 2018

Information regarding patients who were treated for breast cancer in 2018 was extracted from the National Clinical Database (NCD), which is run by Japanese physicians. This database continues from 1975, created by the Japanese Breast Cancer Society (JBCS). A total of 95,620 breast cancer cases were registered. The demographics, clinical characteristics, pathology, surgical treatment, adjuvant chemotherapy, adjuvant endocrine therapy, and radiation therapy of Japanese breast cancer patients were summarized. We made comparisons with other reports to reveal the characteristics of our database. We also described some features in Japanese breast cancer that changed over time. The unique characteristics of breast cancer patients in Japan may provide guidance for future research and improvement in healthcare services.

Bimodal Age Distribution in Cancer Incidence

Cancer is caused by accumulation of genetic changes which include activation of protooncogenes and loss of tumor suppressor genes. The age-specific incidence of cancer in general increases with advancing age. However, some cancers exhibit a bimodal distribution. Commonly recognized cancers with bimodal age distribution include acute lymphoblastic leukemia, osteosarcoma, Hodgkin's lymphoma, germ cell tumors and breast cancer. Delayed infection hypothesis has been used to provide explanation for the early childhood peak in leukemias and lymphomas, whereas the peak at an older age is associated with accumulation of protooncogenes and weakened immune system. Further genetic analysis and histopathological variations point to distinctly different cancers, varying genetically and histologically, which are often combined under a single category of cancers. Tumor characteristics and age distribution of these cancers varies also by population groups and has further implications on cancer screening methods. Although significant advances have been made to explain the bimodal nature of such cancers, the specific genetic mechanisms for each age distribution remain to be elucidated. Further distinction among the different cancer subtypes may lead to improvements in individual risk assessments, prevention and enhancement of treatment strategies.

Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression

Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.

Intrinsic subtypes in Ethiopian breast cancer patient

PURPOSE

The recent development of multi-gene assays for gene expression profiling has contributed significantly to the understanding of the clinically and biologically heterogeneous breast cancer (BC) disease. PAM50 is one of these assays used to stratify BC patients and individualize treatment. The present study was conducted to characterize PAM50-based intrinsic subtypes among Ethiopian BC patients.

PATIENTS AND METHODS

Formalin-fixed paraffin-embedded tissues were collected from 334 BC patients who attended five different Ethiopian health facilities. All samples were assessed using the PAM50 algorithm for intrinsic subtyping.

RESULTS

The tumor samples were classified into PAM50 intrinsic subtypes as follows: 104 samples (31.1%) were luminal A, 91 samples (27.2%) were luminal B, 62 samples (18.6%) were HER2-enriched and 77 samples (23.1%) were basal-like. The intrinsic subtypes were found to be associated with clinical and histopathological parameters such as steroid hormone receptor status, HER2 status, Ki-67 proliferation index and tumor differentiation, but not with age, tumor size or histological type. An immunohistochemistry-based classification of tumors (IHC groups) was found to correlate with intrinsic subtypes.

CONCLUSION

The distribution of the intrinsic subtypes confirms previous immunohistochemistry-based studies from Ethiopia showing potentially endocrine-sensitive tumors in more than half of the patients. Health workers in primary or secondary level health care facilities can be trained to offer endocrine therapy to improve breast cancer care. Additionally, the findings indicate that PAM50-based classification offers a robust method for the molecular classification of tumors in the Ethiopian context.

Postpartum breast cancer has a distinct molecular profile that predicts poor outcomes

Young women's breast cancer (YWBC) has poor prognosis and known interactions with parity. Women diagnosed within 5-10 years of childbirth, defined as postpartum breast cancer (PPBC), have poorer prognosis compared to age, stage, and biologic subtype-matched nulliparous patients. Genomic differences that explain this poor prognosis remain unknown. In this study, using RNA expression data from clinically matched estrogen receptor positive (ER+) cases (n = 16), we observe that ER+ YWBC can be differentiated based on a postpartum or nulliparous diagnosis. The gene expression signatures of PPBC are consistent with increased cell cycle, T-cell activation and reduced estrogen receptor and TP53 signaling. When applied to a large YWBC cohort, these signatures for ER+ PPBC associate with significantly reduced 15-year survival rates in high compared to low expressing cases. Cumulatively these results provide evidence that PPBC is a unique entity within YWBC with poor prognostic phenotypes.

Age-specific incidence rates of breast cancer among Japanese women increasing in a conspicuous bimodal distribution pattern

Breast cancer incidence rates are increasing in East and Southeast Asia, along with the westernisation of reproductive and lifestyle patterns. Such westernisation is thought to be involved in the cumulative exposure of breast tissue to both endogenous and exogenous oestrogen. Immigrant studies among Asian American women indicate that risk factors for breast cancer can be modified. When breast cancer incidence rates were compared with those of corpus uteri and colon among Japanese women in 2005, 2010 and 2015, it is of note that age-specific incidence rates of breast cancer in 5-year age groups clearly increased during the 10-year period in a bimodal distribution pattern, with two peaks in the 45–49 and 60–64 years age groups. From the relevant literature, it is inferred that the low prevalence of obesity and the intake of soy products or isoflavones among Japanese women may contribute to the bimodal distribution pattern by suppressing the extent of increase in breast cancer incidence rates among Japanese postmenopausal women. With regard to dietary habits relating to obesity, it has been globally reported that the intake of high-calorie foods is associated with the incidence of oestrogen receptor-positive breast cancer in both pre- and postmenopausal women, while high-carbohydrate or -milk intake that can enhance the secretion of insulin or insulin-like growth factor 1 is associated with that of oestrogen receptor-negative breast cancer mostly in postmenopausal women. Studies are needed to clarify the aetiology or modifiable factors behind the bimodal incidence rates of breast cancer among Japanese women.

Epidemiology of Basal-like and Luminal Breast Cancers among Black Women in the AMBER Consortium

BACKGROUND

Evidence suggests etiologic heterogeneity among breast cancer subtypes. Previous studies with six-marker IHC classification of intrinsic subtypes included small numbers of black women.

METHODS

Using centralized laboratory results for estrogen receptor (ER), progesterone receptor, HER2, proliferation marker, Ki-67, EGFR, and cytokeratin (CK)5/6, we estimated case-only and case-control ORs for established breast cancer risk factors among cases (n = 2,354) and controls (n = 2,932) in the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. ORs were estimated by ER status and intrinsic subtype using adjusted logistic regression.

RESULTS

Case-only analyses by ER status showed etiologic heterogeneity by age at menarche, parity (vs. nulliparity), and age at first birth. In case-control analyses for intrinsic subtype, increased body mass index and waist-to-hip ratio (WHR) were associated with increased risk of luminal A subtype, whereas older age at menarche and parity, regardless of breastfeeding, were associated with reduced risk. For basal-like cancers, parity without breastfeeding and increasing WHR were associated with increased risk, whereas breastfeeding and age ≥25 years at first birth were associated with reduced risk among parous women. Basal-like and ER^-/HER2⁺ subtypes had earlier age-at-incidence distribution relative to luminal subtypes.

CONCLUSIONS

Breast cancer subtypes showed distinct etiologic profiles in the AMBER consortium, a study of more than 5,000 black women with centrally assessed tumor biospecimens.

IMPACT

Among black women, high WHR and parity without breastfeeding are emerging as important intervention points to reduce the incidence of basal-like breast cancer.