MIMESIS: minimal DNA-methylation signatures to quantify and classify tumor signals in tissue and cell-free DNA samples.

DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. Here we present MIMESIS, a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7200 samples demonstrate the capability of MIMESIS to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To assess our framework for clinical applications, we designed a MIMESIS-informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients' circulation. This study provides evidence that our extremely parsimonious approach can be used to develop cost-effective and highly scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice.

Pan-cancer onco-signatures reveal a novel mitochondrial subtype of luminal breast cancer with specific regulators.

BACKGROUND: Somatic alterations in cancer cause dysregulation of signaling pathways that control cell-cycle progression, apoptosis, and cell growth. The effect of individual alterations in these pathways differs between individual tumors and tumor types. Recognizing driver events is a complex task requiring integrating multiple molecular data, including genomics, epigenomics, and functional genomics. A common hypothesis is that these driver events share similar effects on the hallmarks of cancer. The availability of large-scale multi-omics studies allows for inferring these common effects from data. Once these effects are known, one can then deconvolve in every individual patient whether a given genomics alteration is a driver event. METHODS: Here, we develop a novel data-driven approach to identify shared oncogenic expression signatures among tumors. We aim to identify gene onco-signature for classifying tumor patients in homogeneous subclasses with distinct prognoses and specific genomic alterations. We derive expression pan-cancer onco-signatures from TCGA gene expression data using a discovery set of 9107 primary pan-tumor samples together with respective matched mutational data and a list of known cancer-related genes from COSMIC database. RESULTS: We use the derived ono-signatures to state their prognostic significance and apply them to the TCGA breast cancer dataset as proof of principle of our approach. We uncover a "mitochondrial" sub-group of Luminal patients characterized by its biological features and regulated by specific genetic modulators. Collectively, our results demonstrate the effectiveness of onco-signatures-based methodologies, and they also contribute to a comprehensive understanding of the metabolic heterogeneity of Luminal tumors. CONCLUSIONS: These findings provide novel genomics evidence for developing personalized breast cancer patient treatments. The onco-signature approach, demonstrated here on breast cancer, is general and can be applied to other cancer types.

Menstrual and Reproductive Factors in Association With Breast Cancer Risk in Vietnamese Women: A Case-Control Study.

OBJECTIVES: Though menstrual and reproductive factors have been associated with the risk of breast cancer in many populations, very few studies have been conducted among Vietnamese women. This study aimed to assess the association between menstrual and reproductive factors and the risk of breast cancer in Vietnamese women. METHODS: A retrospective case-control study of 490 breast cancer cases and 468 controls was conducted in Northern Vietnam. Unconditional logistic regression models adjusting for confounders were used to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) for the associations of menstrual and reproductive factors with the risk of breast cancer; overall and by cancer subtype. RESULTS: Among breast cancer patients, the luminal B subtype was the most frequent (48.6%), followed by HER2-overexpressing (24.5%), luminal A (16.7%), and triple-negative breast cancer (TNBC; 10.2%). Among menopausal women, menopausal age at 50 years or older (OR = 1.71, 95% CI: 1.15-2.57 vs. <50 y) was associated with an increased risk of breast cancer. Earlier age at menarche (<13 y) was associated with a significantly increased risk of breast cancer (OR = 2.66, 95% CI: 1.08-7.51) among premenopausal women only and the luminal A subtype of breast cancer (OR = 3.06, 95% CI: 1.04-8.16). Having more than two children was associated with a reduced risk of premenopausal (OR = .42, 95%CI: .21-.83), luminal B (OR = .43, 95% CI: .24-.79), and TNBC (OR = .34, 95% CI: .14-.89). Later menopause was positively associated with the risk of breast cancer with HER2 overexpression (OR = 2.19, 95% CI: 1.14-4.23). CONCLUSION: Associations of menstrual and reproductive factors with breast cancer among Vietnamese women, particularly for among premenopausal women and for the luminal A subtype, are generally consistent with those reported from other countries. These findings suggest that changes in menstrual and reproductive patterns among young Vietnamese women may contribute to the recent rising incidence of breast cancer in Vietnam.

Immune Checkpoint Inhibitors and Novel Immunotherapy Approaches for Breast Cancer.

PURPOSE OF REVIEW: To critically review the existing evidence on immune checkpoint inhibitors (ICIs) in early-stage and metastatic breast cancer and discuss emerging strategies in the different breast cancer subtypes. RECENT FINDINGS: Immunotherapy has become one of the major milestones in contemporary oncology, revolutionizing the treatment of multiple solid tumors. ICI agents combined with chemotherapy have demonstrated significant efficacy in both early-stage and metastatic triple-negative breast cancer. However, only a subgroup of patients responds to those agents and some associated toxicities, although infrequent, can be life-disabling. Emerging data from immunotherapy studies in advanced hormone receptor-positive (HR +) breast cancer as well as HER2-positive disease are arising with mixed results. Although breast cancer has not classically been considered a hot tumor, ICIs have proven to be effective in a subset of breast cancer patients. However, much remains to be learned, and the identification of new biomarkers beyond PD-L1 expression is essential not only to improve the efficacy of ICI but also to identify patients who can avoid them, together with their toxicities and costs.

Tumor subtypes and survival in male breast cancer.

PURPOSE: Male breast cancer is an uncommon disease, and population-based information regarding prognostic factors is limited. Most cases are hormone receptor (HR) positive; however, the association of tumor subtype with overall survival (OS) and breast cancer-specific survival (BCSS) is unclear. METHODS: Using SEER data, we identified men with invasive breast cancer between 2010 and 2017 with known HR and HER2 status. We examined tumor subtypes by patient characteristics and performed multivariate Cox proportional hazards analyses to determine the associations of each variable with OS and BCSS. RESULTS: We included 2389 men with a median follow-up of 43 months (IQR 19-68). Median age was 66 years. Tumor subtype distribution was 84.1% HR+/HER2-, 12.7% HR+/HER2+ , 0.8% HR-/HER2+, and 2.3% triple-negative (TN). In univariate analysis, OS at 5 years was 76.5% for HR+/HER2-, 65.1% for HR+/HER2+ , 84.2% for HR-/HER2+, and 48.1% for TN (p < 0.0001). Of all subtypes, TN had the worst BCSS (p < 0.0001). Stage, tumor subtype and race were significantly associated with OS and BCSS in multivariate analysis. Adjusted Cox hazard ratios for OS by tumor subtype with HR+/HER2- as reference were 1.55 for HR+/HER2+ (p = 0.001), 1.1 for HR-/HER2+ (p = 0.888), and 3.59 for TN (p < 0.001). CONCLUSION: We observed significant differences in survival outcomes by tumor subtype. Poor outcomes among men with HER2+ and TN disease suggest possible under-treatment, aggressive tumor biology, and/or more advanced disease at presentation. Studies to better understand the inferior survival for men with these subtypes are warranted and will likely require international collaboration.

The prognostic significance of metastatic pattern in stage IV male breast cancer at initial diagnosis: a population-based study.

PURPOSE: Metastatic pattern (MP) is a prognostic factor in women with breast cancer. However, the prognostic significance of MP in male breast cancer patients remains unknown. METHODS: Using the SEER database, we gathered demographic information and disease characteristics for men diagnosed with de novo metastatic breast cancer from 2010 to 2017. Metastases to bone, brain, liver, and lung were used to define MP (bone-only, visceral, bone and visceral [BV], or other). Statistical analyses were performed to identify associations between overall survival (OS) and MP, as well as other patient and tumor features. We used multivariate logistic regression to evaluate factors associated with sites of metastases. RESULTS: We included 250 patients. MP distribution was bone = 38.8%, visceral = 14.8%, BV = 33.2%, and other = 13.2%. Median OS for each was bone = 33 months, visceral = 23 months, BV = 20 months, and other = 46 months (p = 0.046). Patients with brain metastases had significantly shorter OS compared with no brain metastases (median OS = 9 months vs. 30 months; p < 0.001). Compared with other subtypes, triple negative had the shortest OS (median 9 months, p < 0.001). Logistic regression modeling revealed that compared with HR+/HER2- breast cancers, HR-/HER2+ had higher odds of liver metastases and triple negative had higher odds of brain metastases. Patients younger than 50 years had a significantly greater risk of developing brain metastases. CONCLUSIONS: MP and tumor subtype can predict OS outcomes in men with metastatic breast cancer at diagnosis. Brain metastases confer very poor prognosis.

Classification of tumor subtypes leveraging constriction-channel based impedance flow cytometry and optical imaging.

As label-free biomarkers, electrical properties of single cells have been widely used for cell-type classification and cell-status evaluation. However, as intrinsic bioelectrical markers, previously reported membrane capacitance and cytoplasmic resistance (e.g., specific membrane capacitance Cspecific membrane and cytoplasmic conductivity σcytoplasm ) of tumor subtypes were derived from tens of single cells, lacking statistical significance due to low cell numbers. In this study, tumor subtypes were constructed based on phenotype (treatment with 4-methylumbelliferone) or genotype (knockdown of ROCK1) modifications and then aspirated through a constriction-channel based impedance flow cytometry to characterize single-cell Cspecific membrane and σcytoplasm . Thousands of single tumor cells with phenotype modifications were measured, resulting in significant differences in 1.64 ± 0.43 µF/cm2 vs. 1.55 ± 0.47 µF/cm2 of Cspecific membrane and 0.96 ± 0.37 S/m vs. 1.24 ± 0.47 S/m of σcytoplasm for 95C cells (792 cells of 95C-control vs. 1529 cells of 95C-pheno-mod); 2.56 ± 0.88 µF/cm2 vs. 2.33 ± 0.56 µF/cm2 of Cspecific membrane and 0.83 ± 0.18 S/m vs. 0.93 ± 0.25 S/m of σcytoplasm for H1299 cells (962 cells of H1299-control vs. 637 cells of H1299-pheno-mod). Furthermore, thousands of single tumor cells with genotype modifications were measured, resulting in significant differences in 3.82 ± 0.92 vs. 3.18 ± 0.47 µF/cm2 of Cspecific membrane and 0.47 ± 0.05 vs. 0.52 ± 0.05 S/m of σcytoplasm (1100 cells of A549-control vs. 1100 cells of A549-geno-mod). These results indicate that as intrinsic bioelectrical markers, specific membrane capacitance and cytoplasmic conductivity can be used to classify tumor subtypes.

MOGSA: Integrative Single Sample Gene-set Analysis of Multiple Omics Data.

Gene-set analysis (GSA) summarizes individual molecular measurements to more interpretable pathways or gene-sets and has become an indispensable step in the interpretation of large-scale omics data. However, GSA methods are limited to the analysis of single omics data. Here, we introduce a new computation method termed multi-omics gene-set analysis (MOGSA), a multivariate single sample gene-set analysis method that integrates multiple experimental and molecular data types measured over the same set of samples. The method learns a low dimensional representation of most variant correlated features (genes, proteins, etc.) across multiple omics data sets, transforms the features onto the same scale and calculates an integrated gene-set score from the most informative features in each data type. MOGSA does not require filtering data to the intersection of features (gene IDs), therefore, all molecular features, including those that lack annotation may be included in the analysis. Using simulated data, we demonstrate that integrating multiple diverse sources of molecular data increases the power to discover subtle changes in gene-sets and may reduce the impact of unreliable information in any single data type. Using real experimental data, we demonstrate three use-cases of MOGSA. First, we show how to remove a source of noise (technical or biological) in integrative MOGSA of NCI60 transcriptome and proteome data. Second, we apply MOGSA to discover similarities and differences in mRNA, protein and phosphorylation profiles of a small study of stem cell lines and assess the influence of each data type or feature on the total gene-set score. Finally, we apply MOGSA to cluster analysis and show that three molecular subtypes are robustly discovered when copy number variation and mRNA data of 308 bladder cancers from The Cancer Genome Atlas are integrated using MOGSA. MOGSA is available in the Bioconductor R package "mogsa."

Preclinical Models to Study Obesity and Breast Cancer in Females: Considerations, Caveats, and Tools.

Obesity increases the risk for breast cancer and is associated with poor outcomes for cancer patients. A variety of rodent models have been used to investigate these relationships; however, key differences in experimental approaches, as well as unique aspects of rodent physiology lead to variability in how these valuable models are implemented. We combine expertise in the development and implementation of preclinical models of obesity and breast cancer to disseminate effective practices for studies that integrate these fields. In this review, we share, based on our experience, key considerations for model selection, highlighting important technical nuances and tips for use of preclinical models in studies that integrate obesity with breast cancer risk and progression. We describe relevant mouse and rat paradigms, specifically highlighting differences in breast tumor subtypes, estrogen production, and strategies to manipulate hormone levels. We also outline options for diet composition and housing environments to promote obesity in female rodents. While we have applied our experience to understanding obesity-associated breast cancer, the experimental variables we incorporate have relevance to multiple fields that investigate women's health.

Capturing colorectal cancer inter-tumor heterogeneity in patient-derived xenograft (PDX) models.

Patient-derived xenograft (PDX) models have become an important asset in translational cancer research. However, to provide a robust preclinical platform, PDXs need to accommodate the tumor heterogeneity that is observed in patients. Colorectal cancer (CRC) can be stratified into four consensus molecular subtypes (CMS) with distinct biological and clinical features. Surprisingly, using a set of CRC patients, we revealed the partial representation of tumor heterogeneity in PDX models. The epithelial subtypes, the largest subgroups of CRC subtype, were very ineffective in establishing PDXs, indicating the need for further optimization to develop an effective personalized therapeutic approach to CRC. Moreover, we showed that tumor cell proliferation was associated with successful PDX establishment and able to distinguish patient with poor clinical outcomes within CMS2 group.

Associations between mammographic density and tumor characteristics in Chinese women with breast cancer.

PURPOSE: Mammographic density (MD) is a strong risk factor for breast cancer, yet its relationship with tumor characteristics is not well established, particularly in Asian populations. METHODS: MD was assessed from a total of 2001 Chinese breast cancer patients using Breast Imaging Reporting and Data System (BI-RADS) categories. Molecular subtypes were defined using immunohistochemical status on ER, PR, HER2, and Ki-67, as well as tumor grade. Multinomial logistic regression was used to test associations between MD and molecular subtype (luminal A = reference) adjusting for age, body mass index (BMI), menopausal status, parity, and nodal status. RESULTS: The mean age at diagnosis was 51.7 years (SD = 10.7) and the average BMI was 24.7 kg/m2 (SD = 3.8). The distribution of BI-RADS categories was 7.4% A = almost entirely fat, 24.2% B = scattered fibroglandular dense, 49.4% C = heterogeneously dense, and 19.0% D = extremely dense. Compared to women with BI-RADS = A/B, women with BI-RADS = D were more likely to have HER2-enriched tumors (OR = 1.81, 95% CI 1.08-3.06, p = 0.03), regardless of menopausal status. The association was only observed in women with normal (< 25 kg/m2) BMI (OR = 2.43, 95% CI 1.24-4.76, p < 0.01), but not among overweight/obese women (OR: 0.98, 95% CI 0.38-2.52, p = 0.96). CONCLUSIONS: Among Chinese women with normal BMI, higher breast density was associated with HER2-enriched tumors. The results may partially explain the higher proportion of HER2+ tumors previously reported in Asian women.

Prognostic role of body mass index is different according to menopausal status and tumor subtype in breast cancer patients.

PURPOSE: Although controversial, obesity and underweight may have a negative impact on breast cancer outcome. However, the relationship between body mass index (BMI) and breast cancer outcomes according to tumor subtype and menopausal status remains unclear. METHODS: This study investigated the association between BMI and breast cancer outcome in stage I-III breast cancer patients. The relationships were further evaluated according to tumor subtype and menopausal status. RESULTS: A total of 5919 patients, 3475 (58.7%) hormone receptor (HR)(+) human epidermal growth factor receptor 2 (HER2)(-), 608 (10.3%) HR(+)HER2(+), 621 (10.5%) HR(-)HER2(+), and 1079 (18.2%) HR(-)HER2(-) were included. Underweight and obesity had a negative impact on relapse-free survival but did not affect overall survival. Importantly, the prognostic role of BMI was different according to tumor subtype and menopausal status. In HR(+)HER2(-) patients, underweight was associated with poor relapse-free survival and overall survival in pre-menopausal women. In contrast, obesity had negative impact on relapse-free survival and overall survival in HR(+)HER2(-) post-menopausal patients. Underweight may have a negative prognostic role in HR(+)HER2(+) patients. However, BMI did not impact the outcome of HR(-)HER2(+) and HR(-)HER2(-) patients. CONCLUSIONS: The impact of BMI on breast cancer outcome was dependent on tumor subtype and menopausal status. In HR(+)HER2(-) patients, underweight and obesity had a negative prognostic role in pre-menopausal and post-menopausal women, respectively. These findings in Asian population should be further evaluated and compared in Western population.

Outcomes in patients with small node-negative invasive breast cancer.

PURPOSE: There is controversy whether systemic therapy is warranted in patients with small node-negative tumors, especially among those with HER2+ and triple negative breast cancers (TNBC). In this study we sought to compare survival and recurrence rates (RR) in patients with T1mi,a,bN0M0 breast cancer by tumor type. METHODS: Review of a prospectively maintained data base between January 1, 2000 through December 31, 2013 identified 71 patients with HER2+ tumors, 545 with hormone receptor (HR)+ /HER2- tumors, and 45 with TNBC. The three groups were compared with respect to RR, disease-free survival (DFS), and overall survival (OS). Patients with HER2+ disease and TNBC who received chemotherapy were compared to those who did not. RESULTS: At mean follow-up of 4.9 years, the 5-year OS was 95% and 5-year DFS was 98%. RR for HER2+ , HR+ /HER2- , and TNBC was 7.0%, 3.7%, and 4.4% respectively (P = 0.2). There was no significant difference in OS (P = 0.9) and DFS (P = 0.4) amongst the three groups. On multivariable analysis, use of adjuvant chemotherapy was not associated with improvement in DFS or OS. When patients with HER2+ breast cancer and TNBC who received chemotherapy were compared to those who did not, there was no difference in death rates (P = 0.3). CONCLUSIONS: Patients with T1mi,a,bN0M0 invasive breast cancer have an excellent prognosis. The three molecular subtypes differed significantly in age, tumor size, and tumor grade, but had similar RR, DFS, and OS. Chemotherapy was not associated with improved survival. Tumor subtype may not influence recurrence and survival in such small early stage tumors.

Obesity and survival in the neoadjuvant breast cancer setting: role of tumor subtype in an ethnically diverse population.

BACKGROUND: Obesity may negatively affect survival in breast cancer (BC), but studies are conflicting, and associations may vary by tumor subtypes and race/ethnicity groups. METHODS: In a retrospective review, we identified 273 women with invasive BC administered Adriamycin/Taxane-based neoadjuvant chemotherapy from 2004 to 2016 with body mass index (BMI) data at diagnosis. Obesity was defined as BMI ≥30. Associations between obesity and event-free survival (EFS), using STEEP events, and overall survival (OS), using all-cause mortality, were assessed overall and stratified by tumor subtype [[Hormone Receptor Positive (HR+)/HER2-, HER2+, and Triple-Negative Breast Cancer (TNBC])] in our diverse population. RESULTS: Median follow-up was 32.6 months (range 5.7-137.8 months). Overall, obesity was associated with worse EFS (HR 1.71, 95% CI 1.03-2.84, p = 0.04) and a trend towards worse OS (p = 0.13). In HR+/HER2- disease (n = 135), there was an interaction between obesity and hormonal therapy with respect to OS but not EFS. In those receiving tamoxifen (n = 33), obesity was associated with worse OS (HR 9.27, 95% CI 0.96-89.3, p = 0.05). In those receiving an aromatase inhibitor (n = 89), there was no association between obesity and OS. In TNBC (n = 44), obesity was associated with worse EFS (HR 2.62, 95% CI 1.03-6.66, p = 0.04) and a trend towards worse OS (p = 0.06). In HER2+ disease (n = 94), obesity was associated with a trend towards worse EFS (HR 3.37, 95% CI 0.97-11.72, p = 0.06) but not OS. Race/ethnicity was not associated with survival in any subtype, and there were no interactions with obesity on survival. CONCLUSIONS: Obesity may negatively impact survival, with differences among tumor subtypes.

Differences in breast cancer incidence among young women aged 20-49 years by stage and tumor characteristics, age, race, and ethnicity, 2004-2013.

PURPOSE: Younger women diagnosed with breast cancer have poorer prognoses and higher mortality compared to older women. Young black women have higher incidence rates of breast cancer and more aggressive subtypes than women of other races/ethnicities. In this study, we examined recent trends and variations in breast cancer incidence among young women in the United States. METHODS: Using 2004-2013 National Program of Cancer Registries and Surveillance, Epidemiology, and End Results Program data, we calculated breast cancer incidence rates and trends and examined variations in stage, grade, and tumor subtype by age and race/ethnicity among young women aged 20-49 years. RESULTS: The majority of breast cancer cases occurred in women aged 40-44 and 45-49 years (77.3%). Among women aged < 45 years, breast cancer incidence was highest among black women. Incidence trends increased from 2004 to 2013 for Asian or Pacific Islander (API) women and white women aged 20-34 years. Black, American Indian or Alaska Native, and Hispanic women had higher proportions of cases diagnosed at later stages than white and API women. Black women had a higher proportion of grade III-IV tumors than other racial/ethnic groups. Across all age groups, incidence rates for triple-negative breast cancer were significantly higher in black women than women of other races/ethnicities, and this disparity increased with age. CONCLUSIONS: Breast cancer among young women is a highly heterogeneous disease. Differences in tumor characteristics by age and race/ethnicity suggest opportunities for further research into personal and cultural factors that may influence breast cancer risk among younger women.

Age-related terminal duct lobular unit involution in benign tissues from Chinese breast cancer patients with luminal and triple-negative tumors.

BACKGROUND: Terminal duct lobular unit (TDLU) involution is a physiological process of breast tissue aging characterized by a reduction in the epithelial component. In studies of women with benign breast disease, researchers have found that age-matched women with lower levels of TDLU involution are at increased risk of developing breast cancer. We previously showed that breast cancer cases with core basal phenotype (CBP; estrogen receptor negative [ER-], progesterone receptor-negative [PR-], human epidermal growth factor receptor 2-negative [HER2-], cytokeratins (CK 5 or CK5/6)-positive [CK5/6+] and/or epidermal growth factor receptor-positive [EGFR+]) tumors had significantly reduced TDLU involution compared with cases with luminal A (ER+ and/or PR+, HER2-, CK5/6-, EGFR-) tumors from a population-based case-control study in Poland. We evaluated the association of TDLU involution with tumor subtypes in an independent population of women in China, where the breast cancer incidence rate, prevalence of known risk factors, and mammographic breast density are thought to be markedly different from those of Polish women. METHODS: We performed morphometric assessment of TDLUs by using three reproducible semiquantitative measures that inversely correlate with TDLU involution (TDLU count/100 mm2, TDLU span in micrometer, and acini count/TDLU) by examining benign tissue blocks from 254 age-matched luminal A and 250 triple-negative (TN; ER-, PR-, HER2-, including 125 CBP) breast cancer cases treated in a tertiary hospital in Beijing, China. RESULTS: Overall, we found that TN and particularly CBP cases tended to have greater TDLU measures (less involution) than luminal A cases in logistic regression models accounting for age, body mass index, parity, and tumor grade. The strongest association was observed for tertiles of acini count among younger women (aged <50 years) (CBP vs. luminal A; ORtrend 2.11, 95% CI 1.22-3.67, P = 0.008). CONCLUSIONS: These data extend previous findings that TN/CBP breast cancers are associated with reduced TDLU involution in surrounding breast parenchyma compared with luminal A cases among Chinese women, providing further support for differences in the pathogenesis of these tumor subtypes.

Prognostic impact of metastatic pattern in stage IV breast cancer at initial diagnosis.

PURPOSE: To analyze the prognostic influence of metastatic pattern (MP) compared with other biologic and clinical factors in stage IV breast cancer at initial diagnosis (BCID) and evaluate factors associated with specific sites of metastases (SSM). METHODS: We evaluated women with stage IV BCID with known metastatic sites, reported to the Surveillance, Epidemiology and End Results program from 2010 to 2013. MP was categorized as bone-only, visceral, bone and visceral (BV), and other. Univariate and multivariate analyses determined the effects of each variable on overall survival (OS). Logistic regression examined factors associated with SSM. RESULTS: We included 9143 patients. Bone represented 37.5% of patients, visceral 21.9%, BV 28.8%, and other 11.9%. Median OS by MP was as follows: bone 38 months, visceral 21 months, BV 19 months, and other 33 months (P < 0.0001). Univariate analysis showed that higher number of metastatic sites had worse prognosis. In multivariate analysis, older age (hazard ratio 1.9), black race (hazard ratio 1.17), grade 3/4 tumors (hazard ratio 1.6), triple-negative (hazard ratio 2.24), BV MP (hazard ratio 2.07), and unmarried patients (hazard ratio 1.25) had significantly shorter OS. As compared with HR+/HER2- tumors, triple-negative and HR-/HER2+ had higher odds of brain, liver, lung, and other metastases. HR+/HER2+ had higher odds of liver metastases. All three subtypes had lower odds of bone metastases. CONCLUSIONS: There were substantial differences in OS according to MP. Tumor subtypes have a clear influence among other factors on SSM. We identified several prognostic factors that could guide therapy selection in treatment naïve patients.

Emerging power of proteomics for delineation of intrinsic tumor subtypes and resistance mechanisms to anti-cancer therapies.

INTRODUCTION: Despite extreme genetic heterogeneity, tumors often show similar alterations in the expression, stability, and activation of proteins important in oncogenic signaling pathways. Thus, classifying tumor samples according to shared proteomic features may help facilitate the identification of cancer subtypes predictive of therapeutic responses and prognostic for patient outcomes. Meanwhile, understanding mechanisms of intrinsic and acquired resistance to anti-cancer therapies at the protein level may prove crucial to devising reversal strategies. Areas covered: Herein, we review recent advances in quantitative proteomic technology and their applications in studies to identify intrinsic tumor subtypes of various tumors, to illuminate mechanistic aspects of pharmacological and oncogenic adaptations, and to highlight interaction targets for anti-cancer compounds and cancer-addicted proteins. Expert commentary: Quantitative proteomic technologies are being successfully employed to classify tumor samples into distinct intrinsic subtypes, to improve existing DNA/RNA based classification methods, and to evaluate the activation status of key signaling pathways.

[Role of PDLIM4 and c-Src in Breast Cancer Progression].

High heterogeneity is characteristic of oncology diseases, often complicating the choice of optimal anticancer treatment. One cancer type may combine tumors differing in histogenesis, genetic lesions, and mechanism of cell transformation. Differences in the mechanism of cell malignant transformation result in specifics of cancer cell metabolism and sensitivity to various agents, including anticancer treatments. Hence, the molecular subtype of a tumor is essential to know for choosing the optimal therapeutic strategy. The review considers the role actin-associated proteins and tyrosine kinases, in particular, PDLIM4 and Src kinase, play in the formation of pathological signaling pathways.

Proposed therapeutic strategy for adult low-grade glioma based on aggressive tumor resection.

OBJECT There is no standard therapeutic strategy for low-grade glioma (LGG). The authors hypothesized that adjuvant therapy might not be necessary for LGG cases in which total radiological resection was achieved. Accordingly, they established a treatment strategy based on the extent of resection (EOR) and the MIB-1 index: patients with a high EOR and low MIB-1 index were observed without postoperative treatment, whereas those with a low EOR and/or high MIB-1 index received radiotherapy (RT) and/or chemotherapy. In the present retrospective study, the authors reviewed clinical data on patients with primarily diagnosed LGGs who had been treated according to the above-mentioned strategy, and they validated the treatment policy. Given their results, they will establish a new treatment strategy for LGGs stratified by EOR, histological subtype, and molecular status. METHODS One hundred fifty-three patients with diagnosed LGG who had undergone resection or biopsy at Tokyo Women's Medical University between January 2000 and August 2010 were analyzed. The patients consisted of 84 men and 69 women, all with ages ≥ 15 years. A total of 146 patients underwent surgical removal of the tumor, and 7 patients underwent biopsy. RESULTS Postoperative RT and nitrosourea-based chemotherapy were administered in 48 and 35 patients, respectively. Extent of resection was significantly associated with both overall survival (OS; p = 0.0096) and progression-free survival (PFS; p = 0.0007) in patients with diffuse astrocytoma but not in those with oligodendroglial subtypes. Chemotherapy significantly prolonged PFS, especially in patients with oligodendroglial subtypes (p = 0.0009). Patients with a mutant IDH1 gene had significantly longer OS (p = 0.034). Multivariate analysis did not identify MIB-1 index or RT as prognostic factors, but it did identify chemotherapy as a prognostic factor for PFS and EOR as a prognostic factor for OS and PFS. CONCLUSIONS The findings demonstrated that EOR was significantly correlated with patient survival; thus, one should aim for maximum tumor resection. In addition, patients with a higher EOR can be safely observed without adjuvant therapy. For patients with partial resection, postoperative chemotherapy should be administered for those with oligodendroglial subtypes, and repeat resection should be considered for those with astrocytic tumors. More aggressive treatment with RT and chemotherapy may be required for patients with a poor prognosis, such as those with diffuse astrocytoma, 1p/19q nondeleted tumors, or IDH1 wild-type oligodendroglial tumors with partial resection.