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Objective: Deep learning (DL) has shown promising results for improving mammographic breast cancer diagnosis. However, the impact of artificial intelligence (AI) on the breast cancer screening process has not yet been fully elucidated in terms of potential workload reduction. We aim to assess if AI-based triaging of breast cancer screening mammograms could reduce the radiologist's workload with non-inferior sensitivity. Methods: PubMed, EMBASE, Cochrane Central, and Web of Science databases were systematically searched for studies that evaluated AI algorithms on computer-aided triage of breast cancer screening mammograms. We extracted data from homogenous studies and performed a proportion meta-analysis with a random-effects model to examine the radiologist's workload reduction (proportion of low-risk mammograms that could be theoretically ruled out from human's assessment) and the software's sensitivity to breast cancer detection. Results: Thirteen studies were selected for full review, and three studies that used the same commercially available DL algorithm were included in the meta-analysis. In the 156,852 examinations included, the threshold of 7 was identified as optimal. With these parameters, radiologist workload decreased by 68.3% (95%CI 0.655–0.711, I ² = 98.76%, p < 0.001), while achieving a sensitivity of 93.1% (95%CI 0.882–0.979, I ² = 83.86%, p = 0.002) and a specificity of 68.7% (95% CI 0.684–0.723, I ² = 97.5%, p < 0.01). Conclusions: The deployment of DL computer-aided triage of breast cancer screening mammograms reduces the radiology workload while maintaining high sensitivity. Although the implementation of AI remains complex and heterogeneous, it is a promising tool to optimize healthcare resources. [ABSTRACT FROM AUTHOR]

Cardiac tumors are rare and encompass a variety of presentations. Clinical symptoms are usually nonspecific, but they can present as obstructive, embolic, or constitutional symptoms. Treatment options and prognosis vary highly depending on the subtype, tumor size, and location. Surgical resection is usually the first-line therapy, except for cardiac lymphomas, and provides favorable long-term prognosis in most benign tumors. Cardiac sarcomas, however, are usually diagnosed in advanced stages, and the treatment relies on a multimodal approach with chemotherapy and radiotherapy. Metastatic cardiac tumors are usually related to advanced disease and carry an overall poor prognosis. [ABSTRACT FROM AUTHOR]

Induced oncoproteins degradation provides an attractive anti-cancer modality. Activation of anaphase-promoting complex (APC/CCDH1) prevents cell-cycle entry by targeting crucial mitotic proteins for degradation. Phosphorylation of its co-activator CDH1 modulates the E3 ligase activity, but little is known about its regulation after phosphorylation and how to effectively harness APC/CCDH1 activity to treat cancer. Peptidyl-prolyl cis-trans isomerase NIMA-interacting 1 (PIN1)-catalyzed phosphorylation-dependent cis-trans prolyl isomerization drives tumor malignancy. However, the mechanisms controlling its protein turnover remain elusive. Through proteomic screens and structural characterizations, we identify a reciprocal antagonism of PIN1-APC/CCDH1 mediated by domain-oriented phosphorylation-dependent dual interactions as a fundamental mechanism governing mitotic protein stability and cell-cycle entry. Remarkably, combined PIN1 and cyclin-dependent protein kinases (CDKs) inhibition creates a positive feedback loop of PIN1 inhibition and APC/CCDH1 activation to irreversibly degrade PIN1 and other crucial mitotic proteins, which force permanent cell-cycle exit and trigger anti-tumor immunity, translating into synergistic efficacy against triple-negative breast cancer. Unveiling the regulation of mitotic protein degradation is crucial for cancer therapy. Here, the authors reveal that a reciprocal inhibition of PIN1-APC/CCDH1 controls the cell cycle and mitotic protein degradation, offering a synergistic anti-tumor strategy. [ABSTRACT FROM AUTHOR]

PURPOSE: Poly ADP-ribose polymerase inhibitors (PARPi) are approved for patients with human epidermal growth factor receptor 2–negative metastatic breast cancer (mBC) and germline pathogenic/likely pathogenic variant (hereafter mutation) in the BRCA1 / 2 genes (g BRCA); however, clinical benefit has also been demonstrated in mBC with somatic BRCA1 / 2 mutations (s BRCA) or germline PALB2 mutations (g PALB2). This study aims to describe the genomic landscape of homologous recombination repair (HRR) gene alterations in mBC and assess PARPi treatment outcomes for patients with g BRCA compared with other HRR genes and by status of a novel homologous recombination deficiency signature (HRDsig). METHODS: A real-world (RW) clinico-genomic database (CGDB) of comprehensive genomic profiling (CGP) linked to deidentified, electronic health record–derived clinical data was used. CGP was analyzed for HRR genes and HRDsig. The CGDB enabled cohort characterization and outcomes analyses of 177 patients exposed to PARPi. RW progression-free survival (rwPFS) and RW overall survival (rwOS) were compared. RESULTS: Of 28,920 patients with mBC, g BRCA was detected in 3.4%, whereas the population with any BRCA alteration or g PALB2 increased to 9.5%. HRDsig+ represented 21% of patients with mBC. BRCA and g PALB2 had higher levels of biallelic loss and HRDsig+ than other HRR alterations. Outcomes on PARPi were assessed for 177 patients, and g BRCA and s BRCA / gPALB2 cohorts were similar: g BRCA versus s BRCA /g PALB2 rwPFS was 6.3 versus 5.4 months (hazard ratio [HR], 1.37 [0.77-2.43]); rwOS was 16.2 versus 21.2 months (HR, 1.45 [0.74-2.86]). Additionally, patients with HRDsig+ versus HRDsig– had longer rwPFS (6.3 v 2.8 months; HR, 0.62 [0.42-0.92]) and numerically longer rwOS (17.8 v 13.0 months; HR, 0.72 [0.46-1.14]). CONCLUSION: Patients with s BRCA and g PALB2 derive similar benefit from PARPi as those with g BRCA alterations. In combination, HRDsig+, s BRCA , and g PALB2 represent an additional 19% of mBC that can potentially benefit from PARPi. Randomized trials exploring a more inclusive biomarker such as HRDsig are warranted. This is real-world evidence supporting benefit of PARPi in sBRCA, gPALB2, and HRDsig. [ABSTRACT FROM AUTHOR]

Approximately 5% to 10% of women diagnosed with breast cancer will have a pathogenic variant (PV) in a hereditary cancer susceptibility gene, and this has significant implications for the management of these patients and their relatives. Despite the benefits of genetic testing, many eligible patients with breast cancer never undergo testing because of various barriers, including complicated testing criteria such as those from the National Comprehensive Cancer Network (NCCN). In 2019, the American Society of Breast Surgeons (ASBrS) proposed germline genetic testing for all patients with breast cancer to increase the identification of PV carriers. In 2020, a Mayo Clinic study highlighted the limitations of these 2 genetic testing guidelines (NCCN and ASBrS) and proposed a hybrid approach of testing all women diagnosed with breast cancer by the age of 65 years and using NCCN criteria for older patients. This commentary presents an updated analysis of the Mayo Clinic data and discusses the rationale for using the age of 60 years rather than 65 years as the cutoff for this hybrid approach. Using an age at diagnosis of ≤60 or ≤65 years for the universal testing of patients with breast cancer detected more PVs (11.9% [16 of 134] and 15.7% [21 of 134], respectively) in comparison with using the NCCN criteria. Lowering the age for universal testing from 65 to 60 years maintained the sensitivity of detecting a PV at >90% while sparing testing for an additional 10% of women. Compared with the testing of all patients, the hybrid approach would allow 31% of all women with breast cancer to forgo testing and result in fewer variants of uncertain significance identified and, therefore, would decrease the chance of harm from misinterpretation of these variants. The identification of pathogenic variants in high‐risk breast cancer genes has a significant impact on the management of patients with breast cancer and their relatives, yet many women do not receive genetic testing because of various barriers, with one of the major reasons being complex genetic testing criteria. Testing every single patient with breast cancer is not cost‐effective and has the potential for harm through the mismanagement of benign or ambiguous genetic testing results. This commentary argues that a hybrid approach of testing all patients below a certain age threshold while restricting testing on the basis of guidelines for an older population is a better approach. [ABSTRACT FROM AUTHOR]