Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis.

Breast cancer is a prevalent form of cancer worldwide, and the current standard screening method, mammography, often requires invasive biopsy procedures for further assessment. Recent research has explored microRNAs (miRNAs) in circulating blood as potential biomarkers for early breast cancer diagnosis. In this study, we employed a multi-modal spectroscopy approach, combining attenuated total reflection Fourier transform infrared (ATR-FTIR) and surface-enhanced Raman scattering (SERS) to comprehensively characterize the full-spectrum fingerprints of RNA biomarkers in the blood serum of breast cancer patients. The sensitivity of conventional FTIR and Raman spectroscopy was enhanced by ATR-FTIR and SERS through the utilization of a diamond ATR crystal and silver-coated silicon nanopillars, respectively. Moreover, a wider measurement wavelength range was achieved with the multi-modal approach than with a single spectroscopic method alone. We have shown the results on 91 clinical samples, which comprised 44 malignant and 47 benign cases. Principal component analysis (PCA) was performed on the ATR-FTIR, SERS, and multi-modal data. From the peak analysis, we gained insights into biomolecular absorption and scattering-related features, which aid in the differentiation of malignant and benign samples. Applying 32 machine learning algorithms to the PCA results, we identified key molecular fingerprints and demonstrated that the multi-modal approach outperforms individual techniques, achieving higher average validation accuracy (95.1%), blind test accuracy (91.6%), specificity (94.7%), sensitivity (95.5%), and F-score (94.8%). The support vector machine (SVM) model showed the best area under the curve (AUC) characterization value of 0.9979, indicating excellent performance. These findings highlight the potential of the multi-modal spectroscopy approach as an accurate, reliable, and rapid method for distinguishing between malignant and benign breast tumors in women. Such a label-free approach holds promise for improving early breast cancer diagnosis and patient outcomes.

Alterations to DNA methylation patterns induced by chemotherapy treatment are associated with negative impacts on the olfactory pathway.

BACKGROUND: Exposure to cytotoxic chemotherapy treatment may alter DNA methylation (DNAm) in breast cancer patients. METHODS: We performed DNAm analysis in 125 breast cancer patients with blood drawn before and after chemotherapy, using the Illumina MethylationEPIC array. DNAm changes of 588,798 individual CpGs (including 41,207 promoter regions) were evaluated using linear regression models adjusted for monocyte proportion. Gene set enrichment analyses (GSEA) were conducted to identify key Gene Ontology (GO) biological processes or Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with chemotherapy. Results were validated in a separate cohort of breast cancer patients who were treated (n = 1273) and not treated (n = 872) by chemotherapy (1808 blood, 337 saliva). RESULTS: A total of 141 differentially methylated CpGs and 11 promoters were significantly associated with chemotherapy after multiple testing corrections in both the paired sample and single time point analyses. GSEA of promoter regions (pre-ranked by test statistics) identified six suppressed biological processes (p < 4.67e-8) related to sensory perception and detection of chemical stimuli, including smell perception (GO:0007606, GO:0007608, GO:0009593, GO:0050906, GO:0050907, and GO:0050911). The same six biological processes were significantly suppressed in the validation dataset (p < 9.02e-14). The KEGG pathway olfactory transduction (hsa04740) was also found to be significantly suppressed (ppaired-samples = 1.72e-9, psingle-timepoint-blood = 2.03e-15 and psingle-timepoint-saliva = 7.52e-56). CONCLUSION: The enrichment of imprinted genes within biological processes and pathways suggests a biological mechanism by which chemotherapy could affect the perception of smell.

How Asian Breast Cancer Patients Experience Unequal Incidence of Chemotherapy Side Effects: A Look at Ethnic Disparities in Febrile Neutropenia Rates.

The majority of published findings on chemotherapy-induced febrile neutropenia (FN) are restricted to three ethnic groups: Asians, Caucasians, and African Americans. In this two-part study, we examined FN incidence and risk factors in Chinese, Malay, and Indian chemotherapy-treated breast cancer (BC) patients. Hospital records or ICD codes were used to identify patients with FN. In both the Singapore Breast Cancer Cohort (SGBCC) and the Joint Breast Cancer Registry (JBCR), the time of the first FN from the start of chemotherapy was estimated using Cox regression. Multinomial regression was used to evaluate differences in various characteristics across ethnicities. FN was observed in 170 of 1014 patients in SGBCC. The Cox model showed that non-Chinese were at higher risk of developing FN (HRMalay [95% CI]:2.04 [1.44-2.88], p < 0.001; HRIndian:1.88 [1.11-3.18], p = 0.018). In JBCR, FN was observed in 965 of 7449 patients. Univariable Cox models identified ethnicity, a lower baseline absolute neutrophil count, non-luminal A proxy subtypes, and anthracycline-containing regimens as risk factors. Disparities across ethnicities' risk (HRMalay:1.29 [1.07-1.54], p = 0.006; HRIndian:1.50 [1.19-1.88], p < 0.001) remained significant even after further adjustments. Finally, an age-adjusted multinomial model showed that Malays (p = 0.006) and Indians (p = 0.009) were significantly more likely to develop multiple episodes of FN during treatment. Ethnic differences in chemotherapy-induced FN among BC patients exist. Further studies can focus on investigating pharmacogenetic differences across ethnicities.

Label-free detection of MiRNA biomarkers using broadband multi-resonant infrared metasurfaces for early breast cancer diagnosis.

Breast cancer is the most prevalent cancer globally. Early detection is crucial and can be achieved by detecting cancer biomarkers in blood, such as circulating miRNAs (microRNAs). In this study, we present a label-free detection method based on broadband multi-resonant infrared metasurface for surface-enhanced infrared absorption (SEIRA) spectroscopy to detect miRNAs. The SEIRA resonances were optimized to match the miRNA biomarker fingerprint regions in the range of 800 to 2000 cm-1 and 2800 to 3500 cm-1, resulting in a simulated resonance enhancement of up to 103 times. Nine patient samples (six cancerous and three non-cancerous) were measured using SEIRA multi-well sensor chips. A novel analysis method, SEIRA-AR, was also developed to benchmark the results against industry standards, such as quantitative reverse transcription polymerase chain reaction (RT-qPCR) and next-generation sequencing (NGS). Our results showed an excellent linear correlation with a Pearson's r value of up to 0.99 and an R Squared value of up to 0.98. This study represents the first use of a SEIRA sensor for biomarker detection on clinical breast cancer samples and introduces an analysis method that produces results comparable to industry standards. Our findings pave the way for routine cancer diagnosis in the future. Additionally, the method discussed can be generalized to other biosensing activities involving two-step binding processes with complementary molecule-capturing agents.

Dependency of NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis.

Cancer cells undergo transcriptional reprogramming to drive tumor progression and metastasis. Using cancer cell lines and patient-derived tumor organoids, we demonstrate that loss of the negative elongation factor (NELF) complex inhibits breast cancer development through downregulating epithelial-mesenchymal transition (EMT) and stemness-associated genes. Quantitative multiplexed Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins (qPLEX-RIME) further reveals a significant rewiring of NELF-E-associated chromatin partners as a function of EMT and a co-option of NELF-E with the key EMT transcription factor SLUG. Accordingly, loss of NELF-E leads to impaired SLUG binding on chromatin. Through integrative transcriptomic and genomic analyses, we identify the histone acetyltransferase, KAT2B, as a key functional target of NELF-E-SLUG. Genetic and pharmacological inactivation of KAT2B ameliorate the expression of EMT markers, phenocopying NELF ablation. Elevated expression of NELF-E and KAT2B is associated with poorer prognosis in breast cancer patients, highlighting the clinical relevance of our findings. Taken together, we uncover a crucial role of the NELF-E-SLUG-KAT2B epigenetic axis in breast cancer carcinogenesis.

A novel survival prediction signature outperforms PAM50 and artificial intelligence-based feature-selection methods.

The robustness of a breast cancer gene signature, the super-proliferation set (SPS), is initially tested and investigated on breast cancer cell lines from the Cancer Cell Line Encyclopaedia (CCLE). Previously, SPS was derived via a meta-analysis of 47 independent breast cancer gene signatures, benchmarked on survival information from clinical data in the NKI dataset. Here, relying on the stability of cell line data and associative prior knowledge, we first demonstrate through Principal Component Analysis (PCA) that SPS prioritizes survival information over secondary subtype information, surpassing both PAM50 and Boruta, an artificial intelligence-based feature-selection algorithm, in this regard. We can also extract higher resolution 'progression' information using SPS, dividing survival outcomes into several clinically relevant stages ('good', 'intermediate', and 'bad) based on different quadrants of the PCA scatterplot. Furthermore, by transferring these 'progression' annotations onto independent clinical datasets, we demonstrate the generalisability of our method on actual patient data. Finally, via the characteristic genetic profiles of each quadrant/stage, we identified efficacious drugs using their gene reversal scores that can shift signatures across quadrants/stages, in a process known as gene signature reversal. This confirms the power of meta-analytical approaches for gene signature inference in breast cancer, as well as the clinical benefit in translating these inferences onto real-world patient data for more targeted therapies.

Profiling Microbial Communities in Idiopathic Granulomatous Mastitis.

Idiopathic granulomatous mastitis (IGM) is a rare and benign inflammatory breast disease with ambiguous aetiology. Contrastingly, lactational mastitis (LM) is commonly diagnosed in breastfeeding women. To investigate IGM aetiology, we profiled the microbial flora of pus and skin in patients with IGM and LM. A total of 26 patients with IGM and 6 patients with LM were included in the study. The 16S rRNA sequencing libraries were constructed from 16S rRNA gene amplified from total DNA extracted from pus and skin swabs in patients with IGM and LM controls. Constructed libraries were multiplexed and paired-end sequenced on HiSeq4000. Metagenomic analysis was conducted using modified microbiome abundance analysis suite customised R-resource for paired pus and skin samples. Microbiome multivariable association analyses were performed using linear models. A total of 21 IGM and 3 LM paired pus and skin samples underwent metagenomic analysis. Bray−Curtis ecological dissimilarity distance showed dissimilarity across four sample types (IGM pus, IGM skin, LM pus, and LM skin; PERMANOVA, p < 0.001). No characteristic dominant genus was observed across the IGM samples. The IGM pus samples were more diverse than corresponding IGM skin samples (Shannon and Simpson index; Wilcoxon paired signed-rank tests, p = 0.022 and p = 0.07). Corynebacterium kroppenstedtii, reportedly associated with IGM in the literature, was higher in IGM pus samples than paired skin samples (Wilcoxon, p = 0.022). Three other species and nineteen genera were statistically significant in paired IGM pus−skin comparison after antibiotic treatment adjustment and multiple comparisons correction. Microbial profiles are unique between patients with IGM and LM. Inter-patient variability and polymicrobial IGM pus samples cannot implicate specific genus or species as an infectious cause for IGM.

Impact of cytochrome P450 2D6 polymorphisms on decision-making and clinical outcomes in adjuvant hormonal therapy for breast cancer.

BACKGROUND: There are concerns that tamoxifen is less effective in Asian women because of the high prevalence of impaired function cytochrome P450 2D6 (CYP2D6) polymor-phisms. AIM: To evaluate how knowledge of CYP2D6 genotype impacted the choice of hormonal agent and how CYP2D6 genotype and agent were associated with clinical outcomes. METHODS: Eighty-two women were recruited. Seventy-eight completed CYP2D6 genotyping and were categorized into poor, intermediate (IM) and extensive or ultra metabolizer phenotypes. Women with poor metabolizer and IM phenotypes were recommended aromatase inhibitors as the preferred agent. RESULTS: More than 70% of the women had an IM phenotype, 32% an extensive or ultra metabolizer phenotype, and 0% had a poor metabolizer phenotype. Regardless of genotype, more women opted for aromatase inhibitors. Overall, 80% of women completed 5 years of hormonal therapy. Five women developed recurrence, 3 contralateral breast cancer, 5 died, and 1 was diagnosed with a second primary cancer. Five-year recurrence-free and overall survival were slightly better in women with the extensive or ultra metabolizer phenotype compared to those with the IM phenotype, though not statistically significant [P = 0.743, hazard ratio (HR): 1.441, 95% confidence interval (CI): 0.191 to 10.17 and P = 0.798, HR: 1.327, 95%CI: 0.172 to 9.915, respectively]. Women receiving aromatase inhibitors also appeared to have a better, but also nonsignificant, 5-year recurrence-free and overall survival (P = 0.253, HR: 0.368, 95%CI: 0.031 to 0.258 and P = 0.292, HR: 0.252, 95%CI: 0.005 to 4.951, respectively). CONCLUSION: The IM phenotype was highly prevalent but was not associated with clinical outcome.

Mammography screening is associated with more favourable breast cancer tumour characteristics and better overall survival: case-only analysis of 3739 Asian breast cancer patients.

BACKGROUND: Early detection of breast cancer (BC) through mammography screening (MAM) is known to reduce mortality. We examined the differential effect that mammography has on BC characteristics and overall survival and the sociodemographic determinants of MAM utilization in a multi-ethnic Asian population. METHODS: This study included 3739 BC patients from the Singapore Breast Cancer Cohort (2010-2018). Self-reported sociodemographic characteristics were collected using a structured questionnaire. Clinical data were obtained through medical records. Patients were classified as screeners (last screening mammogram ≤ 2 years before diagnosis), non-screeners (aware but did not attend or last screen > 2years), and those unaware of MAM. Associations between MAM behaviour (MB) and sociodemographic factors and MB and tumour characteristics were examined using multinomial regression. Ten-year overall survival was modelled using Cox regression. RESULTS: Patients unaware of screening were more likely diagnosed with late stage (ORstage III vs stage I (Ref) [95% CI]: 4.94 [3.45-7.07], p < 0.001), high grade (ORpoorly vs well-differentiated (reference): 1.53 [1.06-2.20], p = 0.022), nodal-positive, large size (OR>5cm vs ≤2cm (reference): 5.06 [3.10-8.25], p < 0.001), and HER2-positive tumours (ORHER2-negative vs HER2-positive (reference): 0.72 [0.53-0.97], p = 0.028). Similar trends were observed between screeners and non-screeners with smaller effect sizes. Overall survival was significantly shorter than screeners in the both groups (HRnon-screeners: 1.89 [1.22-2.94], p = 0.005; HRunaware: 2.90 [1.69-4.98], p < 0.001). Non-screeners and those unaware were less health conscious, older, of Malay ethnicity, less highly educated, of lower socioeconomic status, more frequently ever smokers, and less physically active. Among screeners, there were more reported personal histories of benign breast surgeries or gynaecological conditions and positive family history of breast cancer. CONCLUSIONS: Mammography attendance is associated with more favourable BC characteristics and overall survival. Disparities in the utility of MAM services suggest that different strategies may be needed to improve MAM uptake.

Replication Study for the Association of Five SNPs Identified by GWAS and Trastuzumab-Induced Cardiotoxicity in Japanese and Singaporean Cohorts.

Trastuzumab (herceptin) is an effective drug for human epidermal growth factor receptor type 2 (HER2)-positive cancer. However, cardiotoxicity remains a serious complication. In our previous genome-wide association study (GWAS), we identified potential associations for five single nucleotide polymorphisms (SNPs) with trastuzumab-induced cardiotoxicity in a Japanese population. To validate this association, here we performed replication studies using Japanese and Singaporean case-control cohorts (Japan: 6 cases and 206 controls; Singapore: 22 cases and 178 controls). Although none of the SNPs showed a statistically significant association with trastuzumab-induced cardiotoxicity, we show that three (rs8032978, rs7406710 and rs9316695) and four (rs8032978, rs7406710, rs28415722 and rs11932853) SNPs had an effect in the same direction in the Japanese and the Singaporean cohort, respectively, as that in our previous study. Combining the previous study with the current replication studies, we find a strong association for two SNPs, rs8032978 and rs7406710, with trastuzumab-induced cardiotoxicity (Pcombined = 4.92 × 10-5 and 5.50 × 10-5, respectively). These data suggest that rs8032978 and rs7406710 could be predictive markers of trastuzumab-induced cardiotoxicity in Japanese and Singaporean populations, and support their potential use in clinical risk assessment. These findings offer a first step toward the development of clinically available markers for the potential risk of trastuzumab-induced cardiotoxicity as well as an improved understanding of the pathogenesis of this complication.

Hypoxia induces HIF1α-dependent epigenetic vulnerability in triple negative breast cancer to confer immune effector dysfunction and resistance to anti-PD-1 immunotherapy.

The hypoxic tumor microenvironment has been implicated in immune escape, but the underlying mechanism remains elusive. Using an in vitro culture system modeling human T cell dysfunction and exhaustion in triple-negative breast cancer (TNBC), we find that hypoxia suppresses immune effector gene expression, including in T and NK cells, resulting in immune effector cell dysfunction and resistance to immunotherapy. We demonstrate that hypoxia-induced factor 1α (HIF1α) interaction with HDAC1 and concurrent PRC2 dependency causes chromatin remolding resulting in epigenetic suppression of effector genes and subsequent immune dysfunction. Targeting HIF1α and the associated epigenetic machinery can reverse the immune effector dysfunction and overcome resistance to PD-1 blockade, as demonstrated both in vitro and in vivo using syngeneic and humanized mice models. These findings identify a HIF1α-mediated epigenetic mechanism in immune dysfunction and provide a potential strategy to overcome immune resistance in TNBC.

IFI16-dependent STING signaling is a crucial regulator of anti-HER2 immune response in HER2+ breast cancer.

Relapse to anti-HER2 monoclonal antibody (mAb) therapies, such as trastuzumab in HER2+ breast cancer (BC), is associated with residual disease progression due to resistance to therapy. Here, we identify interferon-γ inducible protein 16 (IFI16)-dependent STING signaling as a significant determinant of trastuzumab responses in HER2+ BC. We show that down-regulation of immune-regulated genes (IRG) is specifically associated with poor survival of HER2+, but not other BC subtypes. Among IRG, IFI16 is identified as a direct target of EZH2, the underexpression of which leads to deficient STING activation and downstream CXCL10/11 expression in response to trastuzumab treatment. Dual inhibition of EZH2 and histone deacetylase (HDAC) significantly activates IFI16-dependent immune responses to trastuzumab. Notably, a combination of a novel histone methylation inhibitor with an HDAC inhibitor induces complete tumor eradication and long-term T cell memory in a HER2+ BC mouse model. Our findings demonstrate an epigenetic regulatory mechanism suppressing the expression of the IFI16-CXCL10/11 signaling pathway that provides a survival advantage to HER2+ BC to confer resistance to trastuzumab treatment.

Can Contrast-Enhanced Spectral Mammography (CESM) Reduce Benign Breast Biopsy?

Objectives: To evaluate the potential of contrast-enhanced spectral mammography (CESM) in reducing benign breast biopsy rate, thereby improving resource utilization. To explore its potential as a value-adding modality in the management of BI-RADS 4/5 lesions. Materials and Methods: This was a prospective study conducted between July 2016 and September 2018. Patients with BI-RADS 4/5 lesions detected on conventional imaging (mammogram, digital breast tomosynthesis, and ultrasound) were enrolled for adjunct CESM. Histopathologic correlation was done for all lesions. Additional suspicious lesions detected on CESM were all identified on second-look ultrasound and subsequently biopsied. Images were evaluated independently by two radiologists trained in breast imaging using BI-RADS classification. Presence of enhancement on CESM, BI-RADS score, and histopathology of each lesion were analyzed and tested with the chi-square/fisher-exact test for statistical significance. Results: The study included 105 lesions in 63 participants-1 man and 62 women, an average age of 53.7 ± 10.8 years. On CESM, 22 (20.9%) of the lesions did not show enhancement. All 22 lesions had been classified as BI-RADS 4A and were subsequently proven to be benign. Of the remaining 83 enhancing lesions, 54 (65.1%) were malignant and 29 (34.9%) were benign (p < 0.05). CESM detected 6 additional lesions which were not identified on initial conventional imaging. Four of these were proven malignant and were in a different quadrant than the primary lesion investigated. Conclusion: There is evidence that the absence of enhancement in CESM strongly favors benignity. It may provide the reporting radiologist with greater confidence in imaging assessment, especially in BI-RADS 4A cases, where a proportion of them are in actuality BI-RADS 3. Greater accuracy of BI-RADS grading can reduce nearly half of benign biopsies and allow better resource allocation. CESM also increases the detection rate of potentially malignant lesions, thereby changing the treatment strategies.

Association between Breast Cancer Polygenic Risk Score and Chemotherapy-Induced Febrile Neutropenia: Null Results.

BACKGROUND: The hypothesis that breast cancer (BC) susceptibility variants are linked to chemotherapy-induced toxicity has been previously explored. Here, we investigated the association between a validated 313-marker-based BC polygenic risk score (PRS) and chemotherapy-induced neutropenia without fever and febrile neutropenia (FNc) in Asian BC patients. METHODS: This observational case-control study of Asian BC patients treated with chemotherapy included 161 FNc patients, 219 neutropenia patients, and 936 patients who did not develop neutropenia. A continuous PRS was calculated by summing weighted risk alleles associated with overall, estrogen receptor- (ER-) positive, and ER-negative BC risk. PRS distributions neutropenia or FNc cases were compared to controls who did not develop neutropenia using two-sample t-tests. Odds ratios (OR) and corresponding 95% confidence intervals were estimated for the associations between PRS (quartiles and per standard deviation (SD) increase) and neutropenia-related outcomes compared to controls. RESULTS: PRS distributions were not significantly different in any of the comparisons. Higher PRSoverall quartiles were negatively correlated with neutropenia or FNc. However, the associations were not statistically significant (PRS per SD increase OR neutropenia: 0.91 [0.79-1.06]; FNc: 0.87 [0.73-1.03]). No dose-dependent trend was observed for the ER-positive weighted PRS (PRSER-pos) and ER-negative weighted PRS (PRSER-neg). CONCLUSION: BC PRS was not strongly associated with chemotherapy-induced neutropenia or FNc.

Relevance of the MHC region for breast cancer susceptibility in Asians.

BACKGROUND: Human leukocyte antigen (HLA) genes play critical roles in immune surveillance, an important defence against tumors. Imputing HLA genotypes from existing single-nucleotide polymorphism datasets is low-cost and efficient. We investigate the relevance of the major histocompatibility complex region in breast cancer susceptibility, using imputed class I and II HLA alleles, in 25,484 women of Asian ancestry. METHODS: A total of 12,901 breast cancer cases and 12,583 controls from 12 case-control studies were included in our pooled analysis. HLA imputation was performed using SNP2HLA on 10,886 quality-controlled variants within the 15-55 Mb region on chromosome 6. HLA alleles (n = 175) with info scores greater than 0.8 and frequencies greater than 0.01 were included (resolution at two-digit level: 71; four-digit level: 104). We studied the associations between HLA alleles and breast cancer risk using logistic regression, adjusting for population structure and age. Associations between HLA alleles and the risk of subtypes of breast cancer (ER-positive, ER-negative, HER2-positive, HER2-negative, early-stage, and late-stage) were examined. RESULTS: We did not observe associations between any HLA allele and breast cancer risk at P < 5e-8; the smallest p value was observed for HLA-C*12:03 (OR = 1.29, P = 1.08e-3). Ninety-five percent of the effect sizes (OR) observed were between 0.90 and 1.23. Similar results were observed when different subtypes of breast cancer were studied (95% of ORs were between 0.85 and 1.18). CONCLUSIONS: No imputed HLA allele was associated with breast cancer risk in our large Asian study. Direct measurement of HLA gene expressions may be required to further explore the associations between HLA genes and breast cancer risk.

Overlap of high-risk individuals predicted by family history, and genetic and non-genetic breast cancer risk prediction models: implications for risk stratification.

BACKGROUND: Family history, and genetic and non-genetic risk factors can stratify women according to their individual risk of developing breast cancer. The extent of overlap between these risk predictors is not clear. METHODS: In this case-only analysis involving 7600 Asian breast cancer patients diagnosed between age 30 and 75 years, we examined identification of high-risk patients based on positive family history, the Gail model 5-year absolute risk [5yAR] above 1.3%, breast cancer predisposition genes (protein-truncating variants [PTV] in ATM, BRCA1, BRCA2, CHEK2, PALB2, BARD1, RAD51C, RAD51D, or TP53), and polygenic risk score (PRS) 5yAR above 1.3%. RESULTS: Correlation between 5yAR (at age of diagnosis) predicted by PRS and the Gail model was low (r=0.27). Fifty-three percent of breast cancer patients (n=4041) were considered high risk by one or more classification criteria. Positive family history, PTV carriership, PRS, or the Gail model identified 1247 (16%), 385 (5%), 2774 (36%), and 1592 (21%) patients who were considered at high risk, respectively. In a subset of 3227 women aged below 50 years, the four models studied identified 470 (15%), 213 (7%), 769 (24%), and 325 (10%) unique patients who were considered at high risk, respectively. For younger women, PRS and PTVs together identified 745 (59% of 1276) high-risk individuals who were not identified by the Gail model or family history. CONCLUSIONS: Family history and genetic and non-genetic risk stratification tools have the potential to complement one another to identify women at high risk.

Associations between Pre-Diagnostic Physical Activity with Breast Cancer Characteristics and Survival.

Physical activity (PA) is known to reduce breast cancer (BC) risk and improve patient prognosis. However, the association between pre-diagnostic PA and the aggressiveness of BC is unclear. We investigated the associations between PA, BC tumour characteristics, and survival. This retrospective observational study included 7688 BC patients from the Singapore Breast Cancer Cohort (2010−2016). PA information from the questionnaire included intensity (light/moderate/vigorous) and duration (<1 h/1−2 h/>2 h per week). A PA score (1−5) incorporating intensity and duration was calculated. Associations between PA score and tumour characteristics such as stage, histological grade, nodal and hormone receptor status were examined using multinomial regression. Moreover, 10-year overall survival was estimated using Cox regression analysis in 6572 patients after excluding patients with invalid survival data and stage IV disease. Breast tumours associated with higher PA score were more likely to be non-invasive (ORinvasive vs. non-invasive(reference) [95% CI]: 0.71 [0.58−0.87], p-trend = 0.001), of lower grade (ORpoorly vs. well differentiated(reference): 0.69 [0.52−0.93], p = 0.014), ER-positive (ORER-negative vs. ER-positive(reference): 0.94 [0.89−1.00], p-trend = 0.049), PR-positive (ORPR-negative vs. PR-positive(reference): 0.82 [0.67−0.99], p = 0.041), HER2-negative (ORHER2-negative vs. HER2-positive(reference): 1.29 [1.02−1.62], p-trend = 0.002), and less likely to be of HER2-overexpressed subtype (ORHER2-overexpressed vs. Luminal A(reference): 0.89 [0.81−0.98], p-trend = 0.018). These associations (odds ratios) were more pronounced among post-menopausal patients. A higher PA score did not improve survival. Higher levels of pre-diagnostic PA were associated with less aggressive tumours in BC patients. This illustrated another benefit of PA in addition to its known role in BC risk reduction.

Impact of Subsidy on the Use of Personalized Medicine in Breast Cancer.

OBJECTIVES: Advances in adjuvant therapy have led to increased survival rates after cancer prognosis. Herceptin, a targeted therapy, had first been introduced to Singapore in 2006. We aimed to assess whether subsidies for Herceptin from 2012 will lead to changes in uptake among HER2-positive patients by socioeconomic groups. METHODS: Random-intercept logistic regression was used to model diagnostic test and Herceptin uptake using the Singapore Breast Cancer Cohort from 2006 to 2018, adjusting for covariates such as education, housing type, and marital status before and after subsidies. Interrupted time series analysis was used to evaluate the impact of Herceptin subsidy on treatment uptake. Concentration index was also computed by ethnicity and education to measure inequality in uptake. RESULTS: We found that the odds of diagnostic testing were not associated with socioeconomic factors. Nevertheless, before subsidies, highest education attained (odds ratio 4.57; 95% confidence interval 1.90-11.02; P<.01) significantly increased the odds of Herceptin uptake. These odds were leveled after the introduction of subsidies to Herceptin treatment from 2012. After subsidy, we also found that Herceptin uptake increased significantly by 11.4% (95% confidence interval 3.47-19.4; P=.016). In addition, inequality of Herceptin use decreased especially among the Indians, where at least 40% were used in the higher educated group before subsidy. CONCLUSIONS: Subsidies have lowered the barriers to Herceptin uptake for marginalized individuals. Having targeted subsidies for socioeconomically disadvantaged groups may work more efficiently in providing ease of access than a blanket subsidy in Herceptin.

Predicting the Likelihood of Carrying a BRCA1 or BRCA2 Mutation in Asian Patients With Breast Cancer.

PURPOSE: With the development of poly (ADP-ribose) polymerase inhibitors for treatment of patients with cancer with an altered BRCA1 or BRCA2 gene, there is an urgent need to ensure that there are appropriate strategies for identifying mutation carriers while balancing the increased demand for and cost of cancer genetics services. To date, the majority of mutation prediction tools have been developed in women of European descent where the age and cancer-subtype distributions are different from that in Asian women. METHODS: In this study, we built a new model (Asian Risk Calculator) for estimating the likelihood of carrying a pathogenic variant in BRCA1 or BRCA2 gene, using germline BRCA genetic testing results in a cross-sectional population-based study of 8,162 Asian patients with breast cancer. We compared the model performance to existing mutation prediction models. The models were evaluated for discrimination and calibration. RESULTS: Asian Risk Calculator included age of diagnosis, ethnicity, bilateral breast cancer, tumor biomarkers, and family history of breast cancer or ovarian cancer as predictors. The inclusion of tumor grade improved significantly the model performance. The full model was calibrated (Hosmer-Lemeshow P value = .614) and discriminated well between BRCA and non-BRCA pathogenic variant carriers (area under receiver operating curve, 0.80; 95% CI, 0.75 to 0.84). Addition of grade to the existing clinical genetic testing criteria targeting patients with breast cancer age younger than 45 years reduced the proportion of patients referred for genetic counseling and testing from 37% to 33% (P value = .003), thereby improving the overall efficacy. CONCLUSION: Population-specific customization of mutation prediction models and clinical genetic testing criteria improved the accuracy of BRCA mutation prediction in Asian patients.

Deep learning applied to breast imaging classification and segmentation with human expert intervention.

PURPOSE: Automatic classification and segmentation of tumors in breast ultrasound images enables better diagnosis and planning treatment strategies for breast cancer patients. METHODS: We collected 953 breast ultrasound images from two open-source datasets and classified them with help of an expert radiologist according to BI-RADS criteria. The data was split into normal, benign and malignant classes. We then used machine learning to develop classification and segmentation algorithms. RESULTS: We found 3.92% of the images across the open-source datasets had erroneous classifications. Post-radiologist intervention, three algorithms were developed based on the classification categories. Classification algorithms distinguished images with healthy breast tissue from those with abnormal tissue with 96% accuracy, and distinguished benign from malignant images with 85% accuracy. Both algorithms generated robust F1 and AUROC metrics. Finally, the masses within images were segmented with an 80.31% DICE score. CONCLUSIONS: Our work illustrates the potential of deep learning algorithms to improve the accuracy of breast ultrasound assessments and to facilitate automated assessments.