Reciprocal antagonism of PIN1-APC/CCDH1 governs mitotic protein stability and cell cycle entry.

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.

Exposing Vulnerabilities in Clinical LLMs Through Data Poisoning Attacks: Case Study in Breast Cancer.

Training Large Language Models (LLMs) with billions of parameters on a dataset and publishing the model for public access is the standard practice currently. Despite their transformative impact on natural language processing, public LLMs present notable vulnerabilities given the source of training data is often web-based or crowdsourced, and hence can be manipulated by perpetrators. We delve into the vulnerabilities of clinical LLMs, particularly BioGPT which is trained on publicly available biomedical literature and clinical notes from MIMIC-III, in the realm of data poisoning attacks. Exploring susceptibility to data poisoning-based attacks on de-identified breast cancer clinical notes, our approach is the first one to assess the extent of such attacks and our findings reveal successful manipulation of LLM outputs. Through this work, we emphasize on the urgency of comprehending these vulnerabilities in LLMs, and encourage the mindful and responsible usage of LLMs in the clinical domain.

Artificial intelligence for triaging of breast cancer screening mammograms and workload reduction: A meta-analysis of a deep learning software.

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, I² = 98.76%, p < 0.001), while achieving a sensitivity of 93.1% (95%CI 0.882-0.979, I² = 83.86%, p = 0.002) and a specificity of 68.7% (95% CI 0.684-0.723, I² = 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.

Metastatic ER+ Breast Cancer: Mechanisms of Resistance and Future Therapeutic Approaches.

Endocrine therapy is the main treatment for hormone receptor-positive (HR+) breast cancer. However, advanced tumors develop resistance to endocrine therapy, rendering it ineffective as the disease progresses. There are several molecular mechanisms of primary and secondary endocrine resistance. Resistance can develop due to either alteration of the estrogen receptor pathway (e.g., ESR1 mutations) or upstream growth factors signaling pathways (e.g., PI3K/Akt/mTOR pathway). Despite progress in the development of molecularly targeted anticancer therapies, the emergence of resistance remains a major limitation and an area of unmet need. In this article, we review the mechanisms of acquired endocrine resistance in HR+ advanced breast cancer and discuss current and future investigational therapeutic approaches.

Homologous Recombination Deficiency Landscape of Breast Cancers and Real-World Effectiveness of Poly ADP-Ribose Polymerase Inhibitors in Patients With Somatic BRCA1/2, Germline PALB2, or Homologous Recombination Deficiency Signature.

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 (gBRCA); however, clinical benefit has also been demonstrated in mBC with somatic BRCA1/2 mutations (sBRCA) or germline PALB2 mutations (gPALB2). 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 gBRCA 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, gBRCA was detected in 3.4%, whereas the population with any BRCA alteration or gPALB2 increased to 9.5%. HRDsig+ represented 21% of patients with mBC. BRCA and gPALB2 had higher levels of biallelic loss and HRDsig+ than other HRR alterations. Outcomes on PARPi were assessed for 177 patients, and gBRCA and sBRCA/gPALB2 cohorts were similar: gBRCA versus sBRCA/gPALB2 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 sBRCA and gPALB2 derive similar benefit from PARPi as those with gBRCA alterations. In combination, HRDsig+, sBRCA, and gPALB2 represent an additional 19% of mBC that can potentially benefit from PARPi. Randomized trials exploring a more inclusive biomarker such as HRDsig are warranted.

Safety and Serum Estradiol Levels in Hormonal Treatments for Vulvovaginal Atrophy in Breast Cancer Survivors: A Systematic Review and Meta-Analysis.

Vulvo-vaginal atrophy (VVA) or genitourinary syndrome of menopause (GSM) is a common condition among breast cancer (BC) patients, especially those undergoing antiestrogen therapy. Despite being an option in refractory cases, the safety of hormonal treatment remains uncertain in this population. The aim of this study was to review the safety and serum estrogen levels of hormonal therapy in patients with BC history presenting with VVA symptoms. Pubmed, Embase, and Cochrane were searched for studies comparing different hormonal treatment options for VVA in breast cancer survivors. Statistical analysis was performed using a random effects model and heterogeneity using Cochran's Q-statistic and the I2 index. We included 17 studies, of which 5 were randomized controlled trials (RCTs). Treatment modalities included in this study were topical vaginal estradiol and estriol preparations, vaginally applied testosterone, DHEA, and ospemifene. We found that, among patients treated with the estriol and estradiol preparations, there was an average increase of 7.67 pg/mL (SMD 7.67 pg/mL; 95% CI -1.00, 16.35; p < .001). Analysis of the testosterone group found temporary peaks of serum estradiol levels, but 1 study showed persistent elevation above normal postmenopausal levels. One study with prasterone revealed no elevation of serum estradiol concentration. One study with ospemifene demonstrated no increase in the risk of BC recurrence. In conclusion, among treatments available for BC survivors, low-dose vaginal estrogen showed the smallest changes in serum estradiol levels and had the most evidence, but safety remains unclear, especially for patients on aromatase inhibitors. Alternative treatments such as ospemifene need more data supporting safety and efficacy. These results suggest that concerns related to cancer recurrence should keep aiming for the lowest possible concentration.

Targeting of microRNA-22 Suppresses Tumor Spread in a Mouse Model of Triple-Negative Breast Cancer.

microRNA-22 (miR-22) is an oncogenic miRNA whose up-regulation promotes epithelial-mesenchymal transition (EMT), tumor invasion, and metastasis in hormone-responsive breast cancer. Here we show that miR-22 plays a key role in triple negative breast cancer (TNBC) by promoting EMT and aggressiveness in 2D and 3D cell models and a mouse xenograft model of human TNBC, respectively. Furthermore, we report that miR-22 inhibition using an LNA-modified antimiR-22 compound is effective in reducing EMT both in vitro and in vivo. Importantly, pharmacologic inhibition of miR-22 suppressed metastatic spread and markedly prolonged survival in mouse xenograft models of metastatic TNBC highlighting the potential of miR-22 silencing as a new therapeutic strategy for the treatment of TNBC.

Comparison of PARPi efficacy according to homologous recombination deficiency biomarkers in patients with ovarian cancer: a systematic review and meta-analysis.

BACKGROUND: Mutations in the BRCA1/2 (BRCA) genes are associated with response to poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi). In addition, there are different homologous recombination deficiency (HRD) biomarkers available in clinical practice [e.g., genome-wide loss-of-heterozygosity (gLOH) and myChoice® score] that identify patients who can benefit from PARPi. Inconsistencies in biomarkers used in PARPi clinical trials make it challenging to identify clinically relevant predictive biomarkers. This study aims to compare clinically available HRD biomarkers in terms of benefits from PARPi. METHODS: We performed database search for phase II or III randomized clinical trials comparing PARPi versus chemotherapy, and meta-analysis using generic inverse variance and a Random Effects model. Patients were classified according to their HRD status: (I) BRCAm (patients with BRCA mutation of germline or somatic origin); (II) non-BRCA HRD [patients BRCA wild-type (wt) with another HRD biomarker-gLOH or myChoice®]; and (III) homologous recombination proficiency (HRP) (BRCAwt and without HRD biomarkers). From those that were BRCAwt, we compared myChoice®+ with gLOH-high. RESULTS: Five studies (3,225 patients) analyzing PARPi in first line setting were included. Patients with BRCAmut had progression-free survival (PFS) with hazard ratio (HR) 0.33 [95% confidence interval (CI): 0.30-0.43]; patients with non-BRCA HRD had a PFS HR 0.49 (95% CI: 0.37-0.65), and patients with HRP had a PFS HR 0.78 (95% CI: 0.58-1.03). Eight studies (5,529 patients) with PARPi including first line and recurrence settings were included. BRCAmut had PFS HR 0.37 (95% CI: 0.30-0.48), BRCAwt & HRD 0.45 (95% CI: 0.37-0.55) and HRP 0.70 (95% CI: 0.57-0.85). Patients with BRCAwt & myChoice® ≥42 had PFS HR 0.43 (95% CI: 0.34-0.56), similar to patients with BRCAwt & gLOH-high with PFS HR 0.42 (95% CI: 0.28-0.62). CONCLUSIONS: Patients with HRD derived significantly more benefit from PARPi when compared to patients with HRP. The benefit of PARPi in patients with HRP tumors was limited. Careful cost-effectiveness analysis, and alternative therapies or clinical trial enrollment should strongly be considered for patients with HRP tumors. Among patients with BRCAwt, a similar benefit was found in patients with gLOH-high and those myChoice®+. The clinical development of further HRD biomarkers (e.g., Sig3) may help identify more patients who benefit from PARPi.

Reciprocal inhibition of PIN1 and APC/CCDH1 controls timely G1/S transition and creates therapeutic vulnerability.

Cyclin-dependent kinases (CDKs) mediated phosphorylation inactivates the anaphase-promoting complex (APC/CCDH1), an E3 ubiquitin ligase that contains the co-activator CDH1, to promote G1/S transition. PIN1 is a phosphorylation-directed proline isomerase and a master cancer signaling regulator. However, little are known about APC/CCDH1 regulation after phosphorylation and about PIN1 ubiquitin ligases. Here we uncover a domain-oriented reciprocal inhibition that controls the timely G1/S transition: The non-phosphorylated APC/CCDH1 E3 ligase targets PIN1 for degradation in G1 phase, restraining G1/S transition; APC/CCDH1 itself, after phosphorylation by CDKs, is inactivated by PIN1-catalyzed isomerization, promoting G1/S transition. In cancer, PIN1 overexpression and APC/CCDH1 inactivation reinforce each other to promote uncontrolled proliferation and tumorigenesis. Importantly, combined PIN1- and CDK4/6-inhibition reactivates APC/CCDH1 resulting in PIN1 degradation and an insurmountable G1 arrest that translates into synergistic anti-tumor activity against triple-negative breast cancer in vivo. Reciprocal inhibition of PIN1 and APC/CCDH1 is a novel mechanism to control timely G1/S transition that can be harnessed for synergistic anti-cancer therapy.

PARP-inhibition reprograms macrophages toward an anti-tumor phenotype.

Poly(ADP)ribosylation inhibitors (PARPis) are toxic to cancer cells with homologous recombination (HR) deficiency but not to HR-proficient cells in the tumor microenvironment (TME), including tumor-associated macrophages (TAMs). As TAMs can promote or inhibit tumor growth, we set out to examine the effects of PARP inhibition on TAMs in BRCA1-related breast cancer (BC). The PARPi olaparib causes reprogramming of TAMs toward higher cytotoxicity and phagocytosis. A PARPi-related surge in NAD+ increases glycolysis, blunts oxidative phosphorylation, and induces reverse mitochondrial electron transport (RET) with an increase in reactive oxygen species (ROS) and transcriptional reprogramming. This reprogramming occurs in the absence or presence of PARP1 or PARP2 and is partially recapitulated by addition of NAD derivative methyl-nicotinamide (MNA). In vivo and ex vivo, the effect of olaparib on TAMs contributes to the anti-tumor efficacy of the PARPi. In vivo blockade of the "don't-eat-me signal" with CD47 antibodies in combination with olaparib improves outcomes in a BRCA1-related BC model.

Mutational Signature 3 Detected from Clinical Panel Sequencing is Associated with Responses to Olaparib in Breast and Ovarian Cancers.

PURPOSE: The identification of patients with homologous recombination deficiency (HRD) beyond BRCA1/2 mutations is an urgent task, as they may benefit from PARP inhibitors. We have previously developed a method to detect mutational signature 3 (Sig3), termed SigMA, associated with HRD from clinical panel sequencing data, that is able to reliably detect HRD from the limited sequencing data derived from gene-focused panel sequencing. EXPERIMENTAL DESIGN: We apply this method to patients from two independent datasets: (i) high-grade serous ovarian cancer and triple-negative breast cancer (TNBC) from a phase Ib trial of the PARP inhibitor olaparib in combination with the PI3K inhibitor buparlisib (BKM120; NCT01623349), and (ii) TNBC patients who received neoadjuvant olaparib in the phase II PETREMAC trial (NCT02624973). RESULTS: We find that Sig3 as detected by SigMA is positively associated with improved progression-free survival and objective responses. In addition, comparison of Sig3 detection in panel and exome-sequencing data from the same patient samples demonstrated highly concordant results and superior performance in comparison with the genomic instability score. CONCLUSIONS: Our analyses demonstrate that HRD can be detected reliably from panel-sequencing data that are obtained as part of routine clinical care, and that this approach can identify patients beyond those with germline BRCA1/2mut who might benefit from PARP inhibitors. Prospective clinical utility testing is warranted.

PARP Inhibitors for Breast Cancer: Germline BRCA1/2 and Beyond.

Poly-adenosine diphosphate ribose polymerase (PARP) inhibitors (PARPi) are approved for BRCA1/2 carriers with HER2-negative breast cancer in the adjuvant setting with a high risk of recurrence as well as the metastatic setting. However, the indications for PARPi are broader for patients with other cancer types (e.g., prostate and ovarian cancer), involving additional biomarkers (e.g., ATM, PALB2, and CHEK) and genomic instability scores. Herein, we summarize the data on PARPi and breast cancer and discuss their use beyond BRCA carriers.

Artificial intelligence for prediction of treatment outcomes in breast cancer: Systematic review of design, reporting standards, and bias.

BACKGROUND: Artificial intelligence (AI) has the potential to personalize treatment strategies for patients with cancer. However, current methodological weaknesses could limit clinical impact. We identified common limitations and suggested potential solutions to facilitate translation of AI to breast cancer management. METHODS: A systematic review was conducted in MEDLINE, Embase, SCOPUS, Google Scholar and PubMed Central in July 2021. Studies investigating the performance of AI to predict outcomes among patients undergoing treatment for breast cancer were included. Algorithm design and adherence to reporting standards were assessed following the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. Risk of bias was assessed by using the Prediction model Risk Of Bias Assessment Tool (PROBAST), and correspondence with authors to assess data and code availability. RESULTS: Our search identified 1,124 studies, of which 64 were included: 58 had a retrospective study design, with 6 studies with a prospective design. Access to datasets and code was severely limited (unavailable in 77% and 88% of studies, respectively). On request, data and code were made available in 28% and 18% of cases, respectively. Ethnicity was often under-reported (not reported in 52 of 64, 81%), as was model calibration (63/64, 99%). The risk of bias was high in 72% (46/64) of the studies, especially because of analysis bias. CONCLUSION: Development of AI algorithms should involve external and prospective validation, with improved code and data availability to enhance reliability and translation of this promising approach. Protocol registration number: PROSPERO - CRD42022292495.

An overview of artificial intelligence in oncology.

Cancer is associated with significant morbimortality globally. Advances in screening, diagnosis, management and survivorship were substantial in the last decades, however, challenges in providing personalized and data-oriented care remain. Artificial intelligence (AI), a branch of computer science used for predictions and automation, has emerged as potential solution to improve the healthcare journey and to promote precision in healthcare. AI applications in oncology include, but are not limited to, optimization of cancer research, improvement of clinical practice (eg., prediction of the association of multiple parameters and outcomes - prognosis and response) and better understanding of tumor molecular biology. In this review, we examine the current state of AI in oncology, including fundamentals, current applications, limitations and future perspectives.

Response in BRCA1 mutation carrier with metastatic pancreatic adenocarcinoma treated with FOLFIRINOX.

A woman in her 50s previously treated for early-stage breast cancer, parotid mucoepidermoid carcinoma and Caroli's disease was diagnosed with stage IV pancreatic ductal adenocarcinoma (PDAC) metastatic to the liver and was found to harbour a BRCA1 germline mutation. She had palliative chemotherapy, initially with 5-fluorouracil, leucovorin, irinotecan and oxaliplatin, and then FOLFIRI and capecitabine, achieving a sustained near-complete response for at least 86 months. Chemotherapy was eventually discontinued when she was diagnosed with a tongue squamous cell carcinoma. Despite withholding systemic therapy, she has maintained a durable response. This is the first report in the English literature showing a sustained duration of response in a patient with PDAC and BRCA1 germline mutation.

Phase 1b Clinical Trial with Alpelisib plus Olaparib for Patients with Advanced Triple-Negative Breast Cancer.

PURPOSE: We had previously reported on the safety and the recommended phase 2 dose (RP2D) of olaparib in combination with the PI3Kα-specific inhibitor alpelisib in patients with high-grade serous ovarian cancer as studied in a phase 1b trial (NCT01623349). Here, we report on the breast cancer cohort from that study. PATIENTS AND METHODS: Eligible patients had recurrent triple-negative breast cancer (TNBC) or recurrent breast cancer of any subtype with a germline BRCA mutation and were enrolled to a dose-escalation or -expansion cohort. After definition of the RP2D, secondary end points included safety and objective response rate (ORR). Exploratory analyses were performed using circulating-free DNA (cfDNA). RESULTS: Seventeen patients with TNBC were enrolled with a median of three prior lines of chemotherapy. The most common treatment-related grade 3-4 adverse events were hyperglycemia (18%) and rash (12%). The ORR was 18% (23% for patients treated at the RP2D) and 59% had disease control. The median duration of response was 7.4 months. Analysis of cfDNA tumor fractions (TFx) revealed that patients with TFx < 15% after completion of the first cycle had a longer progression-free survival compared with those with TFx ≥ 15% (6.0 vs. 0.9 months; P = 0.0001). CONCLUSIONS: Alpelisib in combination with olaparib is tolerable in patients with pre-treated TNBC, with evidence of activity in non-BRCA carriers. cfDNA provided important prognostic information. Results highlight potential synergistic use of a PI3K inhibitor to sensitize HR-proficient (BRCA wild-type) TNBC to PARP inhibition and suggest the potential to expand the use of PARP inhibition beyond BRCA-mutant tumors.

Germline genetic testing in breast cancer: Rationale for the testing of all women diagnosed by the age of 60 years and for risk-based testing of those older than 60 years.

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.

Double-hit monomorphic B-cell lymphoma after liver transplantation.

We report the first case of double-hit (MYC and BCL-6) monomorphic post-transplant lymphoproliferative disorder in a patient status post liver transplantation. Our patient is a 71-year-old man with a past medical history of Budd-Chiari syndrome complicated by cirrhosis and hepatocellular carcinoma. He underwent a deceased donor liver transplantation 2 years prior to presentation and was maintained on tacrolimus and mycophenolate mofetil for immunosuppression. He presented with a 3-week history of classical B-symptoms. Initial workup was notable for elevated lactate dehydrogenase. Abdomen ultrasound revealed multiple hypoechoic lesions, raising suspicion for a post-transplant lymphoproliferative disorder. Biopsy showed pleomorphic large neoplastic cells throughout, consistent with a diagnosis of diffuse large B-cell lymphoma. Cytogenetics then revealed rearrangements in both MYC and BCL-6, consistent with double-hit lymphoma. His immunosuppressive regimen was subsequently tapered and he was started on DA-EPOCH-R (dose-adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin and rituximab) regimen.