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In this study, the impact of the apolipoprotein B mRNA-editing catalytic subunit-like (APOBEC) enzyme APOBEC3B (A3B) on epidermal growth factor receptor (EGFR)-driven lung cancer was assessed. A3B expression in EGFR mutant (EGFRmut) non-small-cell lung cancer (NSCLC) mouse models constrained tumorigenesis, while A3B expression in tumors treated with EGFR-targeted cancer therapy was associated with treatment resistance. Analyses of human NSCLC models treated with EGFR-targeted therapy showed upregulation of A3B and revealed therapy-induced activation of nuclear factor kappa B (NF-κB) as an inducer of A3B expression. Significantly reduced viability was observed with A3B deficiency, and A3B was required for the enrichment of APOBEC mutation signatures, in targeted therapy-treated human NSCLC preclinical models. Upregulation of A3B was confirmed in patients with NSCLC treated with EGFR-targeted therapy. This study uncovers the multifaceted roles of A3B in NSCLC and identifies A3B as a potential target for more durable responses to targeted cancer therapy.

PurposeLynch syndrome is defined by germline pathogenic mutations involving DNA mismatch repair (MMR) genes and linked with the development of MMR-deficient colon and endometrial cancers. Whether breast cancers developing in the context of Lynch syndrome are causally related to MMR deficiency (MMRd), remains controversial. Thus, we explored the morphologic and genomic characteristics of breast cancers occurring in Lynch syndrome individuals.Experimental designA retrospective analysis of 20,110 patients with cancer who underwent multigene panel genetic testing was performed to identify individuals with a likely pathogenic/pathogenic germline variant in MLH1, MSH2, MSH6, or PMS2 who developed breast cancers. The histologic characteristics and IHC assessment of breast cancers for MMR proteins and programmed death-ligand 1 (PD-L1) expression were assessed on cases with available materials. DNA samples from paired tumors and blood were sequenced with Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (≥468 key cancer genes). Microsatellite instability (MSI) status was assessed utilizing MSISensor. Mutational signatures were defined using SigMA.ResultsA total of 272 individuals with Lynch syndrome were identified, 13 (5%) of whom had primary breast cancers. The majority of breast cancers (92%) were hormone receptor-positive tumors. Five (42%) of 12 breast cancers displayed loss of MMR proteins by IHC. Four (36%) of 11 breast cancers subjected to tumor-normal sequencing showed dominant MSI mutational signatures, high tumor mutational burden, and indeterminate (27%) or high MSISensor scores (9%). One patient with metastatic MMRd breast cancer received anti-PD1 therapy and achieved a robust and durable response.ConclusionsA subset of breast cancers developing in individuals with Lynch syndrome are etiologically linked to MMRd and may benefit from anti-PD1/PD-L1 immunotherapy.

Physiologic activation of estrogen receptor [alpha] (ER[alpha]) is mediated by estradiol (E2) binding in the ligand- binding pocket of the receptor, repositioning helix 12 (H12) to facilitate binding of coactivator proteins in the unoccupied coactivator binding groove. In breast cancer, activation of ER[alpha] is often observed through point mutations that lead to the same H12 repositioning in the absence of E2. Through expanded genetic sequencing of breast cancer patients, we identified a collection of mutations located far from H12 but nonetheless capable of promoting E2-independent transcription and breast cancer cell growth. Using machine learning and computational structure analyses, this set of mutants was inferred to act distinctly from the H12-repositioning mutants and instead was associated with conformational changes across the ER[alpha] dimer interface. Through both in vitro and in-cell assays of full-length ER[alpha] protein and isolated ligand-binding domain, we found that these mutants promoted ER[alpha] dimerization, stability, and nuclear localization. Point mutations that selectively disrupted dimerization abrogated E2-independent transcriptional activity of these dimer-promoting mutants. The results reveal a distinct mechanism for activation of ER[alpha] function through enforced receptor dimerization and suggest dimer disruption as a potential therapeutic strategy to treat ER-dependent cancers., Introduction Estrogen receptor [alpha] (ER[alpha]; ESR1), a member of the steroid hormone receptor family, is a hormone-activated transcription factor that is essential for both physiologic mammary gland homeostasis and pathologic [...]

We find that foreign‐born CEOs are more inclined than domestic‐born ones to acquire across borders, and that this inclination is explained by their preference for targets in their birth country. This preference is motivated by foreign‐born CEOs' information advantage in their birth country and by these CEOs' desire to give back to the birth country. CEOs' desire to help their birth country also influences target location, increasing the likelihood of a target in countries that colonized the CEO birth country. The motives that drive acquisitions in acquirer CEOs' birth countries measurably affect the returns of acquirers' shareholders, target premium, and acquisition synergy. Both acquirers' returns and synergy but not target premium are abnormally positive when the motive for an acquisition is a CEO's information advantage in the birth country. Targets premiums but not acquirers' returns and synergy are abnormally positive when the motive for an acquisition is the desire to give back to the CEO's birth country. [ABSTRACT FROM AUTHOR]

PURPOSE: Electronic health records (EHRs) are valuable information repositories that offer insights for enhancing clinical research on breast cancer (BC) using real-world data. The objective of this study was to develop a natural language processing (NLP) model specifically designed to extract structured data from BC pathology reports written in natural language. METHODS: During the initial phase, the algorithm's development cohort comprised 193 pathology reports from 116 patients with BC from 2012 to 2016. A rule-based NLP algorithm was applied to extract 26 variables for analysis and was compared with the manual extraction of data performed by both a data entry specialist and an oncologist. Following the first approach, the data set was expanded to include 513 reports, and a Named Entity Recognition (NER)-NLP model was trained and evaluated using K-fold cross-validation. RESULTS: The first approach led to a concordance analysis, which revealed an 82.9% agreement between the algorithm and the oncologist, whereas the concordance between the data entry specialist and the oncologist was 90.8%. The second training approach introduced the definition of an NER-NLP model, in which the accuracy showed remarkable potential (97.8%). Notably, the model demonstrated remarkable performance, especially for parameters such as estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and Ki-67 (F1-score 1.0). CONCLUSION: The present study aligns with the rapidly evolving field of artificial intelligence (AI) applications in oncology, seeking to expedite the development of complex cancer databases and registries. The results of the model are currently undergoing postprocessing procedures to organize the data into tabular structures, facilitating their utilization in real-world clinical and research endeavors. A high-accuracy NLP model was developed to extract structured data from breast cancer pathology reports. [ABSTRACT FROM AUTHOR]

Background Uterine leiomyosarcoma (uLMS) represents one of the most common sarcoma histotypes, demonstrating an overall dismal prognosis. Previous studies reported uLMS to carry recurrent somatic BRCA2 homozygous deletions, related to significant clinical benefits from the use of PARP inhibitors. Methods To investigate the prevalence in uLMS of genomic alterations (alt) in BRCA2 and other homologous recombination (HR) and DNA damage response (DDR) genes, cBioPortal was accessed and data were retrieved from studies including pan-sarcoma histologies. HR-/DDR-genes included BRCA1 , BRCA2 , ATM , BARD1 , BRIP1 , CHEK1 , CHEK2 , FANCA , FANCB , FANCC , FANCD2 , FANCE , FANCF , FANCG , FANCI , FANCL , FANCM , NBN , PALB2 , RAD51C , RAD51D , RAD50 , and ATR. Only oncogenic/likely oncogenic alterations were included according to OncoKB. Clinical Report and Results We reported a clinical case of a patient affected by a highly pretreated uLMS discussed at the European Institute of Oncology Molecular Tumor Board. A targeted next-generation sequencing panel demonstrated a somatic BRCA2 homozygous deletion (homDel). Upon access to Niraparib, a remarkable response of 15 months was observed before experiencing disease progression. In the genomic query, among 2393 cases, uLMS (n  = 193) displayed 9 of all 31 BRCA2 alt observed, representing the only sarcoma histotype showing an enrichment in BRCA2 alt (4.66%; q  < 0.001). All of 9 BRCA2 alt were represented by homDel, which related to a high fraction of genome altered. Conclusion uLMS displays a significant frequency of somatic BRCA2 alt homDel. Considering their dismal prognosis, further investigation is warranted to test the use of PARPi in uLMS, and particularly in the setting of BRCA1/2 alterations. [ABSTRACT FROM AUTHOR]

Antibody–drug conjugates (ADCs) are anticancer agents with the capacity to selectively deliver their payloads to cancer cells. Antibody–drug conjugates consist of a monoclonal antibody backbone connected by a linker to cytotoxic payloads. Antibody–drug conjugate effect occurs either by directly targeting cancer cells via membrane antigen or through "bystander effect." Antibody–drug conjugates have demonstrated efficacy against various types of tumors, including breast cancer. Ado-trastuzumab emtansine is presently the only approved ADC for the treatment of breast cancer in the early setting, while several ADCs are now approved for metastatic breast cancer. Due to the transformative impact that several ADCs have reported in the setting of advanced breast cancer, researchers are now testing more of such compounds in the early setting, to portend benefits to patients through highly potent anticancer drugs. Ongoing trials hold the potential to transform treatment protocols for early breast cancer in the near future. These trials are aiming at evaluating different treatment modulation approaches, as informed by breast cancer risk of recurrence, including toward treatment de-escalation. Efforts are provided in ongoing clinical trials to identify the patients who will benefit most, to pursue paradigms of precision medicine with the novel ADCs. This review focuses on the potential role of ADCs in early breast cancer, providing an overview of the latest progress in their development and how they are implemented in ongoing clinical trials. [ABSTRACT FROM AUTHOR]

In the last decades, the development of high‐throughput molecular assays has revolutionised cancer diagnostics, paving the way for the concept of personalised cancer medicine. This progress has been driven by the introduction of such technologies through biomarker‐driven oncology trials. In this review, strengths and limitations of various state‐of‐the‐art sequencing technologies, including gene panel sequencing (DNA and RNA), whole‐exome/whole‐genome sequencing and whole‐transcriptome sequencing, are explored, focusing on their ability to identify clinically relevant biomarkers with diagnostic, prognostic and/or predictive impact. This includes the need to assess complex biomarkers, for example microsatellite instability, tumour mutation burden and homologous recombination deficiency, to identify patients suitable for specific therapies, including immunotherapy. Furthermore, the crucial role of biomarker analysis and multidisciplinary molecular tumour boards in selecting patients for trial inclusion is discussed in relation to various trial concepts, including drug repurposing. Recognising that today's exploratory techniques will evolve into tomorrow's routine diagnostics and clinical study inclusion assays, the importance of emerging technologies for multimodal diagnostics, such as proteomics and in vivo drug sensitivity testing, is also discussed. In addition, key regulatory aspects and the importance of patient engagement in all phases of a clinical trial are described. Finally, we propose a set of recommendations for consideration when planning a new precision cancer medicine trial. [ABSTRACT FROM AUTHOR]