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Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the absence of progesterone and estrogen receptors and low (or absent) HER2 expression. TNBC accounts for 15-20% of all breast cancers. It is associated with younger age, a higher mutational burden, and an increased risk of recurrence and mortality. Standard treatment for TNBC primarily relies on cytotoxic agents, such as taxanes, anthracyclines, and platinum compounds for both early and advanced stages of the disease. Several targeted therapies, including bevacizumab and sunitinib, have failed to demonstrate significant clinical benefit in TNBC. The emergence of immune checkpoint inhibitors (ICI) has revolutionized cancer treatment. By stimulating the immune system, ICIs induce a durable anti-tumor response across various solid tumors. TNBC is a particularly promising target for treatment with ICIs due to the higher levels of tumor-infiltrating lymphocytes (TIL), increased PD-L1 expression, and higher mutational burden, which generates tumor-specific neoantigens that activate immune cells. ICIs administered as monotherapy in advanced TNBC yields only a modest response; however, response rates significantly improve when ICIs are combined with cytotoxic agents, particularly in tumors expressing PD-L1. Pembrolizumab is approved for use in both early and advanced TNBC in combination with standard chemotherapy. However, more research is needed to identify more potent biomarkers, and to better elucidate the synergism of ICIs with other targeted agents. In this review, we explore the challenges of immunotherapy in TNBC, examining the mechanisms of tumor progression mediated by immune cells within the tumor microenvironment, and the signaling pathways involved in both primary and acquired resistance. Finally, we provide a comprehensive overview of ongoing clinical trials underway to investigate novel immune-targeted therapies for TNBC.

Single-cell RNA sequencing (scRNA-seq) technology has emerged as a powerful tool for dissecting cellular heterogeneity and understanding the intricate biology of diseases, including cancer. Endometrial cancer (EC) stands out as the most prevalent gynecological malignancy in Europe and the second most diagnosed worldwide, yet its cellular complexity remains poorly understood. In this review, we explore the contributions of scRNA-seq studies to shed light on the tumor cells and cellular landscape of EC. We discuss the diverse tumoral and microenvironmental populations identified through scRNA-seq, highlighting the implications for understanding disease progression. Furthermore, we address potential limitations inherent in scRNA-seq studies, such as technical biases and sample size constraints, emphasizing the need for larger-scale research encompassing a broader spectrum of EC histological subtypes. Notably, a significant proportion of scRNA-seq analyses have focused on primary endometrioid carcinoma tumors, underscoring the need to incorporate additional histological and aggressive types to comprehensively capture the heterogeneity of EC. By critically evaluating the current state of scRNA-seq research in EC, this review underscores the importance of advancing towards more comprehensive studies to accelerate our understanding of this complex disease.

IntroductionTumor-infiltrating lymphocytes (TILs) have predictive and prognostic value in breast cancer (BC) and exert a protective function against tumor growth, indicating that it is susceptible to treatment using adoptive cell transfer of TILs or T cell receptor (TCR)-based therapies. TCR can be used to identify naturally tumor-reactive T cells, but little is known about the differences in the TCR repertoires of CD4+ and CD8+ TILs.MethodsTCR high-throughput sequencing was performed using TILs derived from the initial cultures of 11 BC biopsies and expanded and sorted CD4+ and CD8+ TILs as well as using PBMCs from healthy donors expanded and sorted using the same methodology.ResultsPhysicochemical TCR differences between T cell subsets were observed, as CD4+ TILs presented larger N(D)Nnt TRB sequences and with a higher usage of positively charged residues, although only the latest was also observed in peripheral T cells from healthy individuals. Moreover, in CD4+ TILs, a more restricted TCR repertoire with a higher abundance of similar sequences containing certain amino acid motifs was observed.DiscussionSome differences between CD4+ and CD8+ TCRs were intrinsic to T cell subsets as can also be observed in peripheral T cells from healthy individuals, while other were only found in TILs samples and therefore may be tumor-driven. Notably, the higher similarity among CD4+ TCRs suggests a higher TCR promiscuity in this subset.

De-escalation trials in oncology evaluate therapies that aim to improve the quality of life of patients with low-risk cancer by avoiding overtreatment. Non-inferiority randomized trials are commonly used to investigate de-intensified regimens with similar efficacy to that of standard regimens but with fewer adverse effects (ESMO evidence tier A). In cases where it is not feasible to recruit the number of patients needed for a randomized trial, single-arm prospective studies with a hypothesis of non-inferiority can be conducted as an alternative. Single-arm studies are also commonly used to evaluate novel treatment strategies (ESMO evidence tier B). A single-arm design that includes both non-inferiority and superiority primary objectives will enable the ranking of clinical activity and other parameters such as safety, pharmacokinetics, and pharmacodynamics data. Here, we describe the statistical principles and procedures to support such a strategy. The non-inferiority margin is calculated using the fixed margin method. Sample size and statistical analyses are based on the maximum likelihood method for exponential distributions. We present example analyses in metastatic and adjuvant settings to illustrate the usefulness of our methodology. We also explain its implementation with nonparametric methods. Single-arm designs with non-inferiority and superiority analyses are optimal for proof-of-concept and de-escalation studies in oncology.

IntroductionTumor infiltrating lymphocytes (TILs) are known to be a prognostic and predictive biomarker in breast cancer, particularly in triple negative breast cancer (TNBC) patients. International guidelines have been proposed to evaluate them in the clinical setting as a continuous variable, without a clear defined cut-off. However, there are scenarios where the immune infiltration is heterogeneous that some areas of the patient’s tumour have high numbers of TILs while other areas completely lack them. This spontaneous presentation of a heterogeneous immune infiltration could be a great opportunity to study why some tumours present TILs at diagnosis but others do not, while eliminating inter patient’s differences.MethodsIn this study, we have identified five TNBC patients that showed great TIL heterogeneity, with areas of low (≤5%) and high (≥50%) numbers of TILs in their surgical specimens. To evaluate immune infiltration heterogeneity, we performed and analyzed bulk RNA-sequencing in three independent triplicates from the high and low TIL areas of each patient.ResultsGene expression was homogeneous within the triplicates in each area but was remarkable different between TILs regions. These differences were not only due to the presence of TILs as there were other non-inflammatory genes and pathways differentially expressed between the two areas.DiscussionThis highlights the importance of intratumour heterogeneity driving the immune infiltration, and not patient’s characteristics like the HLA phenotype, germline DNA or immune repertoire.

EBV-specific T cells have been recently described to be involved in fatal encephalitis and myocarditis in cancer patients after immune checkpoint therapies. Here, we report the study of a human triple-negative breast cancer tumor (TNBC) and EBV-transformed B cells obtained from a patient-derived xenograft (PDX) that progressed into a lymphocytic neoplasm named xenograft-associated B-cell lymphoma (XABCL). T-cell receptor (TCR) high-throughput sequencing was performed to monitor the T-cell clonotypes present in the different samples. Forty-three T-cell clonotypes were found infiltrating the XABCL tissue after three passes in mice along 6 months. Eighteen of these (42%) were also found in the TNBC biopsy. TCR infiltrating the XABCL tissue showed a very restricted T-cell repertoire as compared with the biopsy-infiltrating T cells. Consequently, T cells derived from the TNBC biopsy were expanded in the presence of the B-cell line obtained from the XABCL (XABCL-LCL), after which the TCR repertoire obtained was again very restricted, i.e., only certain clonotypes were selected by the B cells. A number of these TCRs had previously been reported as sequences involved in infection, cancer, and/or autoimmunity. We then analyzed the immunopeptidome from the XABCL-LCL, to identify putative B-cell-associated peptides that might have been expanding these T cells. The HLA class I and class II-associated peptides from XABCL-LCL were then compared with published repertoires from LCL of different HLA typing. Proteins from the antigen processing and presentation pathway remained significantly enriched in the XABCL-LCL repertoire. Interestingly, some class II-presented peptides were derived from cancer-related proteins. These results suggest that bystander tumor-infiltrating EBV+ B cells acting as APC may be able to interact with tumor-infiltrating T cells and influence the TCR repertoire in the tumor site.

Breast cancer is the most common tumor in women worldwide, and an increasing public health concern. Knowledge of both protective and negative risk factors is essential for a better understanding of this heterogenous disease. We undertook a review of the recent literature and evaluated the relationship between obesity mediators and breast cancer development depending on menopausal status. Excess weight is now pandemic and has replaced tobacco as the main lifestyle-related risk factor for premature death. Although the prevalence of obesity/overweight has increased globally over the last 50 years, the potential harm attributable to excess fat has generally been underestimated. The relationship between overweight/obesity, breast cancer and overall risk appears to be highly dependent on menopausal status. Thus, obesity increases the risk of breast cancer in postmenopausal women but, conversely, it appears to be protective in premenopausal women. We evaluate the role of different clinical factors potentially involved in this seemingly contradictory relationship, including estrogen, mammogram density, adipokines, insulin-signaling pathway activation, and inflammatory status. A key focus of this review is to better understand the impact of body mass index and menopausal status on these clinical factors and, hence, provide some clarity into the inter-relationships involved in this controversial issue.

Nonrandomized studies are usually excluded from systematic reviews. This could lead to loss of a considerable amount of information on rare diseases. In this article, we explore the impact of excluding nonrandomized studies on the generalizability of meta-analyses results on mucopolysaccharidosis (MPS) disease. A comprehensive search of systematic reviews on MPS patients up to May 2020 was carried out (CRD42020191217). The primary endpoint was the rate of patients excluded from systematic reviews if only randomized studies were considered. Secondary outcomes included the differences in patient and study characteristics between randomized and nonrandomized studies, the methods used to combine data from studies with different designs, and the number of patients excluded from systematic reviews if case reports were not considered. More than 50% of the patients analyzed have been recruited in nonrandomized studies. Patient characteristics, duration of follow-up, and the clinical outcomes evaluated differ between the randomized and nonrandomized studies. There are feasible strategies to combine the data from different randomized and nonrandomized designs. The analyses suggest the relevance of including case reports in the systematic reviews, since the smaller the number of patients in the reference population, the larger the selection bias associated to excluding case reports. Our results recommend including nonrandomized studies in the systematic reviews of MPS to increase the representativeness of the results and to avoid a selection bias. The recommendations obtained from this study should be considered when conducting systematic reviews on rare diseases.

Breast cancer is the cancer with the most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients vs. 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based on the expression levels of five microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the overexpression and downregulation of proteins differently expressed in the serum of breast cancer patients vs. that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue, and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a, miR-497, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of miR-125b, miR-29c, miR-16, miR-1260, and miR-451 was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of miR-16 with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and the potential use of the predictor here described are discussed.

Background: In hormone receptor-positive (HR+)/HER2-negative breast cancer, the HER2-enriched and Basal-like intrinsic subtypes are associated with poor outcome, low response to anti-estrogen therapy and high response to chemotherapy. To date, no validated biomarker exists to identify both molecular entities other than gene expression.Methods: PAM50 subtyping and immunohistochemical data were obtained from 8 independent studies of 1,416 HR+/HER2-negative early breast tumors. A non-luminal disease score (NOLUS) from 0 to 100, based on percentage of estrogen receptor (ER), progesterone receptor (PR) and Ki67 tumor cells, was derived in a combined cohort of 5 studies (training dataset) and tested in a combined cohort of 3 studies. The performance of NOLUS was estimated using Area Under the ROC Curve (AUC).Results: In the training dataset (n = 903) and compared to luminal disease, non-luminal disease had lower percentage of ER-positive cells (median 65.2 vs. 86.2%, p < 0.01) and PR-positive cells (33.2 vs. 56.4%, p < 0.01) and higher percentage of Ki67-positive cells (18.2 vs. 13.1%, p = 0.01). A NOLUS formula was derived: −0.45*ER −0.28*PR +0.27*Ki67 + 73.02. The proportion of non-luminal tumors in NOLUS-positive (≥51.38) and NOLUS-negative (

Background: The minor allele (C) of the single-nucleotide polymorphism (SNP) rs11212617, located near the ataxia telangiectasia mutated (ATM) gene, has been associated with an increased likelihood of treatment success with metformin in type 2 diabetes. We herein investigated whether the same SNP would predict clinical response to neoadjuvant metformin in women with early breast cancer (BC).Methods: DNA was collected from 79 patients included in the intention-to-treat population of the METTEN study, a phase 2 clinical trial of HER2-positive BC patients randomized to receive either metformin combined with anthracycline/taxane-based chemotherapy and trastuzumab or equivalent regimen without metformin, before surgery. SNP rs11212617 genotyping was assessed using allelic discrimination by quantitative polymerase chain reaction.Results: Logistic regression analyses revealed a significant relationship between the rs11212617 genotype and the ability of treatment arms to achieve a pathological complete response (pCR) in patients (odds ratio [OR]genotype×arm = 10.33, 95% confidence interval [CI]: 1.29–82.89, p = 0.028). In the metformin-containing arm, patients bearing the rs11212617 C allele had a significantly higher probability of pCR (ORA/C,C/C = 7.94, 95%CI: 1.60–39.42, p = 0.011). Conversely, no association was found between rs11212617 and clinical response in the reference arm (ORA/C,C/C = 0.77, 95%CI: 0.20–2.92, p = 0.700). After controlling for tumor size and hormone receptor status, the rs11212617 C allele remained a significant predictor of pCR solely in the metformin-containing arm.Conclusions: If reproducible, the rs11212617 C allele might warrant consideration as a predictive clinical biomarker to inform the personalized use of metformin in BC patients.Trial Registration: EU Clinical Trials Register, EudraCT number 2011-000490-30. Registered 28 February 2011, https://www.clinicaltrialsregister.eu/ctr-search/trial/2011-000490-30/ES.

IntroductionThere is debate on which are the best surrogate endpoint and metric to capture treatment effect on overall survival (OS) in RCTs testing immune-checkpoint inhibitors (ICIs).MethodsWe systematically searched for RCTs testing ICIs in patients with advanced solid tumors. Inclusion criteria were: RCTs i) assessing PD-(L)1 and CTLA-4 inhibitors either as monotherapy or in combination with another ICI, and/or targeted therapy, and/or chemotherapy, in patients with advanced solid tumors; ii) randomizing at least 100 patients. We performed a meta-analysis of RCTs to compare the surrogacy value of PFS and modified-PFS (mPFS) for OS in RCTs testing ICIs, when the treatment effect is measured by the hazard ratio (HR) for OS, and by the HR and the ratio of restricted mean survival time (rRMST) for PFS and mPFS.Results61 RCTs (67 treatment comparisons and 36,034 patients) were included in the analysis. In comparisons testing ICI plus chemotherapy, HRPFS and HRmPFS both had a strong surrogacy value (R2 = 0.74 and R2 = 0.81, respectively). In comparisons testing ICI as monotherapy, HRPFS was the best surrogate, although having a moderate correlation (R2 = 0.58). In comparisons testing ICI plus other treatment(s), the associations were very weak for all the surrogate endpoints and treatment effect measures, with R2 ranging from 0.01 to 0.22.ConclusionIn RCTs testing ICIs, the value of potential surrogates for HROS was strongly affected by the type of treatment(s) tested. The evidence available supports HRPFS as the best surrogate, and disproves the use of alternative endpoints, such as the mPFS, or treatment effect measures, such as the RMST.

Background: Academic research is important to face unmet medical needs. The Oncological community encounters many hurdles in setting up multicenter investigator-driven trials mainly due to administrative complexity. The purpose of a network organization at a multinational level is to facilitate clinical trials through standardization, coordination, and education for drug development and regulatory approval.Methods: The application of an European grant foresees the creation of a consortium which aims at facilitating multi-center academic clinical trials.Results: The ERA-NET TRANSCAN Call 2011 on “Validation of biomarkers for personalized cancer medicine” was released on December 2011. This project included Italian, Spanish, French and German centers. The approval process included Consortium constitution, project submission, Clinical Trial Submission, and activation on a national level. The different timescales for submitting study documents in each Country and the misalignment of objections by each Competent Authority CA, generated several requests for changes to the study documents which meant amendments had to be made; as requested by the 2001/20/EC Directive, the alignment of core documents is mandatory. This procedure impacted significantly on study activation timelines. Time to first patient in was 14, 10, 28, and 31 months from the date of submission in Italy, France, Spain, and Germany, respectively. Accrual was stopped on 22nd January 2021 due to an 18F FES shortage as the primary reason but also for having exceeded the project deadlines with consequent exhaustion of the funds allocated for the project.Conclusions: Pharmaceutical companies might be reluctant to fund research projects aimed at treatment individualization if the approval for a wider indication has already been achieved. Academic trials therefore become fundamental for promoting trials which are not attractive to big pharma. It was very difficult and time consuming to activate an academic clinical trial, for this reason, a study may become “old” as new drugs entered into the market. National institutions should promote the development of clinical research infrastructures and network with competence in regulatory, ethical, and legal skills to speed up academic research.

Breast cancer (BC) is the most common malignancy and the second cause of cancer-specific death in women from high-income countries. Recently, gut microbiota dysbiosis emerged as a key player that may directly and/or indirectly influence development, treatment, and prognosis of BC through diverse biological processes: host cell proliferation and death, immune system function, chronic inflammation, oncogenic signalling, hormonal and detoxification pathways. Gut colonisation occurs during the prenatal period and is later diversified over distinct phases throughout life. In newly diagnosed postmenopausal BC patients, an altered faecal microbiota composition has been observed compared with healthy controls. Particularly, β-glucuronidase bacteria seem to modulate the enterohepatic circulation of oestrogens and their resorption, increasing the risk of hormone-dependent BC. Moreover, active phytoestrogens, short-chain fatty acids, lithocholic acid, and cadaverine have been identified as bacterial metabolites influencing the risk and prognosis of BC. As in gut, links are also being made with local microbiota of tumoural and healthy breast tissues. In breast microbiota, different microbial signatures have been reported, with distinct patterns per stage and biological subtype. Total bacterial DNA load was lower in tumour tissue and advanced-stage BC when compared with healthy tissue and early stage BC, respectively. Hypothetically, these findings reflect local dysbiosis, potentially creating an environment that favours breast tumour carcinogenesis (oncogenic trigger), or the natural selection of microorganisms adapted to a specific microenvironment. In this review, we discuss the origin, composition, and dynamic evolution of human microbiota, the links between gut/breast microbiota and BC, and explore the potential implications of metabolomics and pharmacomicrobiomics that might impact BC development and treatment choices toward a more personalised medicine. Finally, we put in perspective the potential limitations and biases regarding the current microbiota research and provide new horizons for stronger accurate translational and clinical studies that are needed to better elucidate the complex network of interactions between host, microorganisms, and drugs in the field of BC.