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Metastasis is the main cause of death for patients with breast cancer. Many studies have characterized the genomic landscape of breast cancer during its early stages. However, there is evidence that genomic alterations are acquired during the evolution of cancers from their early to late stages, and that the genomic landscape of early cancers is not representative of that of lethal cancers 1 – 7 . Here we investigated the landscape of somatic alterations in 617 metastatic breast cancers. Nine driver genes ( TP53 , ESR1 , GATA3 , KMT2C , NCOR1 , AKT1 , NF1 , RIC8A and RB1 ) were more frequently mutated in metastatic breast cancers that expressed hormone receptors (oestrogen and/or progesterone receptors; HR + ) but did not have high levels of HER2 (HER2 − ; n  = 381), when compared to early breast cancers from The Cancer Genome Atlas. In addition, 18 amplicons were more frequently observed in HR + /HER2 − metastatic breast cancers. These cancers showed an increase in mutational signatures S2, S3, S10, S13 and S17. Among the gene alterations that were enriched in HR + /HER2 − metastatic breast cancers, mutations in TP53 , RB1 and NF1 , together with S10, S13 and S17, were associated with poor outcome. Metastatic triple-negative breast cancers showed an increase in the frequency of somatic biallelic loss-of-function mutations in genes related to homologous recombination DNA repair, compared to early triple-negative breast cancers (7% versus 2%). Finally, metastatic breast cancers showed an increase in mutational burden and clonal diversity compared to early breast cancers. Thus, the genomic landscape of metastatic breast cancer is enriched in clinically relevant genomic alterations and is more complex than that of early breast cancer. The identification of genomic alterations associated with poor outcome will allow earlier and better selection of patients who require the use of treatments that are still in clinical trials. The genetic complexity observed in advanced breast cancer suggests that such treatments should be introduced as early as possible in the disease course. Patient data from six clinical trials are used to compare the genomic landscapes of breast cancer metastases with those of primary tumours, revealing an increase in mutational burden and clonal diversity.

Cancer progression is driven in part by genomic alterations 1 . The genomic characterization of cancers has shown interpatient heterogeneity regarding driver alterations 2 , leading to the concept that generation of genomic profiling in patients with cancer could allow the selection of effective therapies 3 , 4 . Although DNA sequencing has been implemented in practice, it remains unclear how to use its results. A total of 1,462 patients with HER2-non-overexpressing metastatic breast cancer were enroled to receive genomic profiling in the SAFIR02-BREAST trial. Two hundred and thirty-eight of these patients were randomized in two trials (nos. NCT02299999 and NCT03386162) comparing the efficacy of maintenance treatment 5 with a targeted therapy matched to genomic alteration. Targeted therapies matched to genomics improves progression-free survival when genomic alterations are classified as level I/II according to the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) 6 (adjusted hazards ratio (HR): 0.41, 90% confidence interval (CI): 0.27–0.61, P  < 0.001), but not when alterations are unselected using ESCAT (adjusted HR: 0.77, 95% CI: 0.56–1.06, P  = 0.109). No improvement in progression-free survival was observed in the targeted therapies arm (unadjusted HR: 1.15, 95% CI: 0.76–1.75) for patients presenting with ESCAT alteration beyond level I/II. Patients with germline BRCA1/2 mutations ( n  = 49) derived high benefit from olaparib (g BRCA1 : HR = 0.36, 90% CI: 0.14–0.89; g BRCA2 : HR = 0.37, 90% CI: 0.17–0.78). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with metastatic breast cancer. Targeted therapies matched to genomics improved progression-free survival when genomic alterations were classified as level I/II (according to ESCAT), and genomics should thus be driven by target actionability in patients with metastatic breast cancer.

ImportanceAs life span has increased among patients with cancer, survivorship has become an important component of breast cancer care. Among survivorship concerns, adequate contraceptive counseling is needed for premenopausal patients who are not seeking to become pregnant.ObjectiveTo examine contraceptive use and chosen methods and to assess factors associated with contraceptive use over time in patients with early breast cancer.Design, Setting, and ParticipantsThe Cancer Toxicity (CANTO) study was a multicenter nationwide prospective cohort study that enrolled women diagnosed with stage I to stage III breast cancer in France between March 2012 and December 2017. This analysis included 2900 premenopausal women who were 50 years of age or younger at diagnosis. Data were analyzed from July 2020 to July 2022.ExposuresContraceptive use and method at diagnosis, shortly after the end of primary treatment (year 1), and during follow-up (year 2).Main Outcomes and MeasuresContraceptive use and methods were longitudinally evaluated at diagnosis, year 1, and year 2 after breast cancer diagnosis. Multivariable logistic regression models were used to assess the associations of clinical, socioeconomic, treatment, adverse effect, and patient-reported outcome variables with contraceptive use after diagnosis.ResultsA total of 2900 patients (mean [SD] age, 43.1 [5.6] years) were included in the analysis; 2050 of 2894 women (70.8%) received chemotherapy, and 2305 of 2880 women (80.0%) received endocrine therapy. After diagnosis, 1182 of 2625 patients (45.0%) at year 1 and 1553 of 2363 patients (65.7%) at year 2 reported consulting with a gynecologist in the previous year. At diagnosis, 1487 of 2744 patients (54.2%) reported contraceptive use, with most patients (921 of 1470 women [62.7%]) using hormonal methods. The use of contraception significantly decreased after diagnosis (911 of 2342 patients [38.9%] at year 1 and 808 of 1961 patients [41.2%] at year 2;P < .001 for trend), when most patients (848 of 900 women [94.2%] at year 1 and 767 of 805 women [95.3%] at year 2) reported use of nonhormonal methods; these methods were primarily reversible mechanical approaches (copper intrauterine devices: 656 of 848 patients [77.4%] at year 1 and 577 of 767 patients [75.2%] at year 2; male condoms: 115 of 848 patients [13.6%] at year 1 and 110 of 767 patients [14.3%] at year 2). In the multivariable model, factors significantly associated with contraceptive use at year 1 included using contraception at diagnosis (adjusted odds ratio [aOR], 4.02; 95% CI, 3.15-5.14), being younger (aOR, 1.09; 95% CI, 1.07-1.13 per decreasing year), having better sexual function (aOR, 1.13; 95% CI, 1.07-1.19 per 10-point increment), having children (aOR, 4.21; 95% CI, 1.80-9.86), reporting the presence of leukorrhea (aOR, 1.32; 95% CI, 1.03-1.70), receiving tamoxifen treatment alone (aOR, 1.39; 95% CI, 1.01-1.92), and consulting with a gynecologist in the previous year (aOR, 1.29; 95% CI, 1.02-1.63). Similar factors were associated with contraceptive use at year 2, with the addition of partnered status (aOR, 1.61; 95% CI, 1.07-2.44).Conclusions and RelevanceFindings from this study support the importance of raising awareness and improving targeted contraceptive counseling for premenopausal women with early breast cancer.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Background: Correctly classifying early estrogen receptor-positive and HER2-negative (ER+/HER2) breast cancer (EBC) cases allows to propose an adapted adjuvant systemic treatment strategy. We developed a new AI-based tool to assess the risk of distant relapse at 5 years for ER+/HER2- EBC patients from pathological slides.Patients and Methods: The discovery dataset (GrandTMA) included 1429 ER+/HER2- EBC patients, with long-term follow-up and an available hematoxylin-eosin and saffron (HES) whole slide image (WSI). A Deep Learning (DL) network was trained to predict metastasis free survival (MFS) at five years, based on the HES WSI only (termed RlapsRisk). A combined score was then built using RlapsRisk and well established prognostic factors. A threshold corresponding to a probability of MFS event of 5% at 5 years was applied to dichotomize patients into low or high-risk groups. The external validation, as well as assessment of the additional prognosis value of the DL model beyond standard clinico-pathologic factors were carried out on an independent, prospective cohort (CANTO, NCT01993498) including 889 HES WSI of ER+/HER2- EBC patients.Results:RlapsRisk was an independent prognostic factor of MFS in multivariable analysis adjusted for established clinico-pathological factors (p<0.005 in GrandTMA and CANTO). Combining RlapsRisk score and the clinico-pathological factors improved the prognostic discrimination as compared to the clinico-pathological factors alone (increment of c-index in the validation set 0.80 versus 0.76, +0.04, p-value < 0.005). After dichotomization, the Combined Model showed a higher cumulative sensitivity on the entire population (0.76 vs 0.61) for an equal dynamic specificity (0.76) in comparison with the clinical score alone.Conclusions:Our deep learning model developed on digitized HES slides provided additional prognostic information as compared to current clinico-pathological factors and has the potential of valuably informing the decision making process in the adjuvant setting when combined with current clinico-pathological factors.Competing Interest StatementSuzette Delaloge reports grants and non-financial support from Pfizer, grants from Novartis, grants and non-financial support from AstraZeneca, grants from Roche Genentech, grants from Lilly, grants from Orion, grants from Amgen, grants from Sanofi, grants from Genomic Health, grants from Servier, grants from MSD, grants from BMS, grants from Pierre Fabre, grants from Exact Sciences, grants from Besins, grants from European Commission grants, grants from French government grants, grants from Fondation ARC grants, grants from Taiho, grants from Elsan, outside the submitted work. Fabrice Andre declares institutional financial interests, research grants with Novartis, Pfizer, Astra Zeneca, Eli Lilly, Daiichi, Roche.

BackgroundWith the development of precision oncology, Molecular Tumor Boards (MTB) are developing in many institutions. However, the implementation of MTB in routine clinical practice has still not been thoroughly studied.Material and methodsSince the first drugs approved for targeted therapies, patient tumor samples were centralized to genomic testing platforms. In our institution, all tumor samples have been analyzed since 2014 by Next Generation Sequencing (NGS). In 2015, we established a regional MTB to discuss patient cases with 1 or more alterations identified by NGS, in genes different from those related to drug approval. We conducted a retrospective comparative analysis to study whether our MTB increased the prescriptions of Molecular Targeted Therapies (MTT) and the inclusions of patients in clinical trials with MTT, in comparison with patients with available NGS data but no MTB discussion.ResultsIn 2014, 86 patients had UGA, but the results were not available to clinicians and not discussed in MTB. During the years 2015 and 2016, 113 patients with an UGA (unreferenced genomic alteration) were discussed in MTB. No patients with an UGA were included in 2014 in a clinical trial, versus 2 (2%) in 2015–2016. 13 patients with an UGA (12%) were treated in 2015–2016 with a MTT whereas in 2014, no patient (p = 0.001).ConclusionsIn this retrospective analysis, we showed that the association of large-scale genomic testing and MTB was feasible, and could increase the prescription of MTT. However, in routine clinical practice, the majority of patients with UGA still do not have access to MTT.

Mismatch repair deficiency (d-MMR)/microsatellite instability (MSI), KRAS, and BRAF mutational status are crucial for treating advanced colorectal cancer patients. Traditional methods like immunohistochemistry or polymerase chain reaction (PCR) can be challenged by artificial intelligence (AI) based on whole slide images (WSI) to predict tumor status. In this systematic review, we evaluated the role of AI in predicting MSI status, KRAS, and BRAF mutations in colorectal cancer. Studies published in PubMed up to June 2023 were included (n = 17), and we reported the risk of bias and the performance for each study. Some studies were impacted by the reduced number of slides included in the data set and the lack of external validation cohorts. Deep learning models for the d-MMR/MSI status showed a good performance in training cohorts (mean AUC = 0.89, [0.74–0.97]) but slightly less than expected in the validation cohort when available (mean AUC = 0.82, [0.63–0.98]). Contrary to the MSI status, the prediction of KRAS and BRAF mutations was less explored with a less robust methodology. The performance was lower, with a maximum of 0.77 in the training cohort, 0.58 in the validation cohort for KRAS, and 0.82 AUC in the training cohort for BRAF.

Endothelial dysfunction is widely implicated in cardiovascular pathological changes and development of vascular disease. In view of the fact that the spontaneous endothelial cell (EC) regeneration is a slow and insufficient process, it is of great interest to explore alternative cell sources capable of generating functional ECs. Vascular smooth muscle cell (SMC) composes the majority of the vascular wall and retains phenotypic plasticity in response to various stimuli. The aim of this study is to test the feasibility of the conversion of SMC into functional EC through the use of reprogramming factors. Human SMCs are first dedifferentiated for 4 days to achieve a vascular progenitor state expressing CD34, by introducing transcription factors OCT4, SOX2, KLF4 and c-MYC. These SMC-derived progenitors are then differentiated along the endothelial lineage. The SMC-converted ECs exhibit typical endothelial markers expression and endothelial functions in vitro , in vivo and in disease model. Further comprehensive analysis indicates that mesenchymal-to-epithelial transition is requisite to initiate SMCs reprogramming into vascular progenitors and that members of the Notch signalling pathway regulate further differentiation of the progenitors into endothelial lineage. Together, we provide the first evidence of the feasibility of the conversion of human SMCs towards endothelial lineage through an intermediate vascular progenitor state induced by reprogramming.

The dynamics of metastatic evolution in clear cell renal cell carcinoma (ccRCC) are complex. We report a case study where tumour heterogeneity resulting from clonal evolution is a frequent feature and could play a role in metastatic dissemination.We used an integrative multiomics strategy combining genomic and transcriptomic data to classify fourteen specimens from spatially different areas of a kidney tumour and three non-primary sites including a vein thrombus and two adrenal metastases.All sites were heterogeneous and polyclonal, each tumour site containing two different aggressive subclonal populations, with differentially expressed genes implicated in distinct biological functions. These are rare primary metastatic samples prior to any medical treatment, where we showed a multiple metastatic seeding of two subclonal populations.Multiple interdependent lineages could be the source of metastatic heterogeneity in ccRCC. By sampling metastases, patients with resistance to therapies could benefit a combination of targeted therapies based on more than one aggressive clone.

Clear cell renal cell carcinoma (ccRCC) has a poor prognosis with a 50% risk of metastases. Little is known about the phenotypic and molecular profiles of metastases regarding their corresponding primary tumors. This study aimed to screen phenotypic and genotypic differences between metastases and their corresponding primary tumors. We selected four cases with available frozen material. The histological, immunohistochemical (VEGFA, CD31, SMA, Ki67, p53, PAR-3), FISH ( VHL gene), next-generation sequencing ( VHL and c-MET genes), multiplex ligation-dependent probe amplification, and array-(comparative genomic hybridization) CGH analyses were realized. Metastases were nodal, hepatic (synchronous), adrenal, and pulmonary (metachronous). High-grade tumor cells were significantly more frequent in metastases ( p  = 0.019). Metastases and high-grade zones of primary tumors shared similar characteristics compared to low-grade zones: a lower microscopic vascular density (43.5 vs 382.5 vessels/mm 2 ; p  = 0.0027), a higher expression of VEGF (73 vs 10%, p  = 0.045), Ki67 (37.6 vs 8.3%; p  = 0.011), and p53 (54 vs 10.6%; p  = 0.081), and a cytoplasmic and membranous PAR-3 staining. Metastases exhibited more chromosomal imbalances than primary tumors in total (18.75 ± 6.8; p  = 0.044) with more genomic gains (13.5 ± 7; p  = 0.013). The loss of chromosome 9 and gain of Xq were found in both primary tumors and metastases but gains of loci or chromosomes 2p, 3q, 5, 8q, 12, and 20 were only found in metastases. The VHL gene status was similar in each tumor couple. Although metastases and primary tumors share common histological features, this study highlights chromosomal differences specific to metastases which could be involved in ccRCC metastatic evolution.