Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level classification by using the quantile function. The quantile function provides a more complete description of the heterogeneity within each image, improving image-level classification. We also adapt image augmentation to the MI framework by randomly selecting cropped regions on which to apply MI aggregation during each epoch of training. This provides a mechanism to study the importance of MI learning. We validate our method on five different classification tasks for breast tumor histology and provide a visualization method for interpreting local image classifications that could lead to future insights into tumor heterogeneity

A model of black cutworm (Agrotis ipsilon) development : a description, uses, and implications

Bibliography: p. 21-22

The MLL-Menin Interaction is a Therapeutic Vulnerability in <em>NUP98</em>-rearranged AML

\ua9 2023 Wolters Kluwer Health. All rights reserved. Chromosomal translocations involving the NUP98 locus are among the most prevalent rearrangements in pediatric acute myeloid leukemia (AML). AML with NUP98 fusions is characterized by high expression of HOXA and MEIS1 genes and is associated with poor clinical outcome. NUP98 fusion proteins are recruited to their target genes by the mixed lineage leukemia (MLL) complex, which involves a direct interaction between MLL and Menin. Here, we show that therapeutic targeting of the Menin-MLL interaction inhibits the propagation of NUP98-rearrranged AML both ex vivo and in vivo. Treatment of primary AML cells with the Menin inhibitor revumenib (SNDX-5613) impairs proliferation and clonogenicity ex vivo in long-term coculture and drives myeloid differentiation. These phenotypic effects are associated with global gene expression changes in primary AML samples that involve the downregulation of many critical NUP98 fusion protein-target genes, such as MEIS1 and CDK6. In addition, Menin inhibition reduces the expression of both wild-type FLT3 and mutated FLT3-ITD, and in combination with FLT3 inhibitor, suppresses patient-derived NUP98-r AML cells in a synergistic manner. Revumenib treatment blocks leukemic engraftment and prevents leukemia-associated death of immunodeficient mice transplanted with NUP98::NSD1 FLT3-ITD-positive patient-derived AML cells. These results demonstrate that NUP98-rearranged AMLs are highly susceptible to inhibition of the MLL-Menin interaction and suggest the inclusion of AML patients harboring NUP98 fusions into the clinical evaluation of Menin inhibitors

Discovery and replication of microRNAs for breast cancer risk using genome-wide profiling

Genome-wide miRNA expression may be useful for predicting breast cancer risk and/or for the early detection of breast cancer

Non-steroidal anti-inflammatory drug use, hormone receptor status, and breast cancer-specific mortality in the Carolina Breast Cancer Study

Epidemiologic studies report a protective association between non-steroidal anti-inflammatory drug (NSAID) use and hormone receptor-positive breast cancer risk, a finding consistent with NSAID-mediated suppression of aromatase-driven estrogen biosynthesis. However, the association between NSAID use and breast cancer-specific mortality is uncertain and it is unknown whether this relationship differs by hormone receptor status. This study comprised 935 invasive breast cancer cases, of which 490 were estrogen receptor (ER)-positive, enrolled between 1996 and 2001 in the Carolina Breast Cancer Study. Self-reported NSAID use in the decade prior to diagnosis was categorized by duration and regularity of use. Differences in tumor size, stage, node, and receptor status by NSAID use were examined using Chi-square tests. Associations between NSAID use and breast cancer-specific mortality were examined using age- and race-adjusted Cox proportional hazards analysis. Tumor characteristics did not differ by NSAID use. Increased duration and regularity of NSAID use was associated with reduced breast cancer-specific mortality in women with ER-positive tumors (long-term regular use (≥8 days/month for ≥ 3 - years) versus no use; hazard ratio (HR) 0.48; 95 % confidence interval (CI) 0.23–0.98), with a statistically significant trend with increasing duration and regularity (p-trend = 0.036). There was no association for ER-negative cases (HR 1.19; 95 %CI 0.50–2.81; p-trend = 0.891). Long-term, regular NSAID use in the decade prior to breast cancer diagnosis was associated with reduced breast cancer-specific mortality in ER-positive cases. If confirmed, these findings support the hypothesis that potential chemopreventive properties of NSAIDs are mediated, at least in part, through suppression of estrogen biosynthesis

A Validated Risk Prediction Model for Breast Cancer in US Black Women

PURPOSE Breast cancer risk prediction models are used to identify high-risk women for early detection, targeted interventions, and enrollment into prevention trials. We sought to develop and evaluate a risk prediction model for breast cancer in US Black women, suitable for use in primary care settings. METHODS Breast cancer relative risks and attributable risks were estimated using data from Black women in three US population-based case-control studies (3,468 breast cancer cases; 3,578 controls age 30-69 years) and combined with SEER age- and race-specific incidence rates, with incorporation of competing mortality, to develop an absolute risk model. The model was validated in prospective data among 51,798 participants of the Black Women’s Health Study, including 1,515 who developed invasive breast cancer. A second risk prediction model was developed on the basis of estrogen receptor (ER)–specific relative risks and attributable risks. Model performance was assessed by calibration (expected/observed cases) and discriminatory accuracy (C-statistic). RESULTS The expected/observed ratio was 1.01 (95% CI, 0.95 to 1.07). Age-adjusted C-statistics were 0.58 (95% CI, 0.56 to 0.59) overall and 0.63 (95% CI, 0.58 to 0.68) among women younger than 40 years. These measures were almost identical in the model based on estrogen receptor–specific relative risks and attributable risks. CONCLUSION Discriminatory accuracy of the new model was similar to that of the most frequently used questionnaire-based breast cancer risk prediction models in White women, suggesting that effective risk stratification for Black women is now possible. This model may be especially valuable for risk stratification of young Black women, who are below the ages at which breast cancer screening is typically begun

Ki-67 Expression in Breast Cancer Tissue Microarrays

Objectives Ki-67 has been proposed to be used as a surrogate marker to differentiate luminal breast carcinomas (BCs). The purpose of this study was to determine the utility of and best approaches for using tissue microarrays (TMAs) and Ki-67 staining to distinguish luminal subtypes in large epidemiology studies of luminal/human epidermal growth factor receptor 2 (HER2)-negative BC. Methods Full-section and TMA (three 0.6-mm cores and two 1.0-mm cores) slides of 109 cases were stained with Ki-67 antibody. We assessed two ways of collapsing TMA cores: a weighted approach and mitotically active approach. Results For cases with at least a single 0.6-mm TMA core (n = 107), 16% were misclassified using a mitotically active approach and 11% using a weighted approach. For cases with at least a single 1.0-mm TMA core (n = 101), 5% were misclassified using either approach. For the 0.6-mm core group, there were 33.3% discordant cases. The number of discordant cases increased from 18% in the group of two cores to 40% in the group of three cores (P =.039). Conclusions Ki-67 tumor heterogeneity was common in luminal/HER2- BC. Using a weighted approach was better than using a mitotically active approach for core to case collapsing. At least a single 1.0-mm core or three 0.6-mm cores are required when designing a study using TMA