29 research outputs found

    Level of HER2/neu amplification in primary tumours and metastases in HER2-positive breast cancer and survival after trastuzumab therapy

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    Abstract Background The level of HER2/neu amplification may vary widely in breast cancers with HER2/neu alteration. The clinical significance of this phenomenon is still unclear. This study was aimed to explore the level of HER2/neu amplification in primary tumours and metastases in HER2-positive metastatic breast cancer (MBC) and its potential impact on survival after a trastuzumab-containing therapy. Methods We retrospectively identified MBC patients treated with a trastuzumab-containing therapy and performed dual-colour FISH on tumour samples from either primary tumour and/or metastasis in a central laboratory. Results We retrieved 110 tumour samples from 91 patients and included 79 tumour samples (primary = 56; metastasis = 23) from 63 patients in the final analysis. We found higher level of HER2/neu amplification in the metastases than in the primary tumours (median HER2/CEP17 ratio: 10.5 vs 7.0, respectively). In 69% of patients ( n = 16) with two tumour samples, the level of HER2/neu amplification was higher in the metastasis than in the paired primary tumour (median HER2/CEP17 ratio: 10.9 vs 8.3, respectively, p = 0.004). The incremental gain in level of HER2/neu amplification was associated with significantly shorter OS after trastuzumab-containing therapy ( p = 0.023, HR 1.014, CI95%: 1.002–1.025). Conclusions The level of HER2/neu amplification tends to increase from the primary tumour to the paired metastases in a significant proportion of patients with HER2-positive MBC. This phenomenon, although still not completely understood, could lead to a shorter OS after trastuzumab therapy

    APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

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    Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project

    High-Salt Diet Exacerbates <i>H. pylori</i> Infection and Increases Gastric Cancer Risks

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    Gastric cancer ranks as the fifth-leading contributor to global cancer incidence and the fourth-highest in terms of cancer-related mortality. Helicobacter pylori (H. pylori) infection leads to inflammation and ulceration, atrophic and chronic gastritis, and eventually, increases the risk of developing gastric adenocarcinoma. In this paper, we delve into the combined impact of a high-salt diet (HSD) and concurrent H. pylori infection, which act as predisposing factors for gastric malignancy. A multitude of mechanisms come into play, fostering the development of gastric adenocarcinoma due to the synergy between an HSD and H. pylori colonization. These encompass the disruption of mucosal barriers, cellular integrity, modulation of H. pylori gene expression, oxidative stress induction, and provocation of inflammatory responses. On the whole, gastric cancer patients were reported to have a higher median sodium intake with respect to healthy controls. H. pylori infection constitutes an additional risk factor, with a particular impact on the population with the highest daily sodium intake. Consequently, drawing from epidemiological discoveries, substantial evidence suggests that diminishing salt intake and employing antibacterial therapeutics could potentially lower the susceptibility to gastric cancer among individuals

    Immune checkpoint inhibitor therapy for hepatocellular carcinoma

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    Liver cancer is the third most common cause of cancer-associated death. Advances in the last decade have provided more options for treating hepatocellular carcinoma. The use of immune checkpoint inhibitors represents a leap forward and broadens the armamentarium for clinicians. In this article, we provide a state-of-the-art review of molecular therapy. We also detail the mechanisms of checkpoint inhibitor therapy, which blocks the interaction of programmed cell death receptor protein with programmed cell death ligand, reducing the immune checkpoint activity on regulatory T cells, thereby inhibiting tumor cell growth

    The Appropriateness of Invasive Ventilation in COVID-19 Positive Cancer Patients: Proposal of a New Prognostic Score

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    Over the last months, as oncology specialists, we have frequently been contacted for estimating prognosis for cancer patients affected by COVID-19 infection. Until now, there have been no clear markers to guide decision making regarding the appropriateness of invasive ventilation in cancer patients affected by COVID-19 infection. We developed a practical tool encompassing a prognostic score, “The Milano Policlinico ONCOVID-ICU score.” The score is composed of three groups of variables: patient’s characteristics such as sex, age, BMI, and comorbidities; oncological variables (treatment intent, life expectancy, on or off-treatment status); and clinical parameters in association with laboratory values (the Sequential Organ Failure Assessment (SOFA) score and D-dimer). The SOFA score includes six different clinical parameters and during the first few days of ICU admissions has an important prognostic role. The oncological history should never represent, per se, a contraindication to intensive care and must be considered together with other variables, such as laboratory values, clinical parameters, and patient characteristics, in order to make the hardest but best possible choice. To our knowledge, “The Milano Policlinico ONCOVID-ICU score” is the first prognostic score proposed in this setting of patients and requires further validation. This tool may be useful to assess the prognosis of cancer patients in critical conditions

    Impact of BMI on Survival Outcomes of Immunotherapy in Solid Tumors: A Systematic Review

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    Growing research has focused on obesity as a prognostic factor during therapy with immune-checkpoint inhibitors (ICIs). The role of body-mass index (BMI) in predicting response and toxicity to ICIs is not clear, as studies have shown inconsistent results and significant interpretation biases. We performed a systematic review to evaluate the relationship between BMI and survival outcomes during ICIs, with a side focus on the incidence of immune-related adverse events (irAEs). A total of 17 studies were included in this systematic review. Altogether, the current evidence does not support a clearly positive association of BMI with survival outcomes. Regarding toxicities, available studies confirm a superimposable rate of irAEs among obese and normal weight patients. Intrinsic limitations of the analyzed studies include the retrospective nature, the heterogeneity of patients’ cohorts, and differences in BMI categorization for obese patients across different studies. These factors might explain the heterogeneity of available results, and the subsequent absence of a well-established role of baseline BMI on the efficacy of ICIs among cancer patients. Further prospective studies are needed, in order to clarify the role of obesity in cancer patients treated with immunotherapy

    The Tumor Microenvironment and the Estrogen Loop in Thyroid Cancer

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    Thyroid cancer (TC) cells employ multiple signaling pathways, such as PI3K/AKT/mTOR and RAS/Raf/MAPK, fostering cell proliferation, survival and metastasis. Through a complex interplay with immune cells, inflammatory mediators and stroma, TC cells support an immunosuppressive, inflamed, pro-carcinogenic TME. Moreover, the participation of estrogens in TC pathogenesis has previously been hypothesized, in view of the higher TC incidence observed among females. In this respect, the interactions between estrogens and the TME in TC could represent a relevant, unexplored area of research. We thereby collectively reviewed the available evidence concerning the potential carcinogenic role of estrogens in TC, specifically focusing on their crosstalk with the TME
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