Littérature scientifique sur le sujet « Marcatori di neoplasie pancreatiche »

SommarioL’incidenza delle neoplasie neuroendocrine (NEN) sta incrementando significativamente, mentre la sopravvivenza dei pazienti non migliora con la stessa velocità, a causa di diagnosi tardive e della mancanza di criteri prognostici consolidati in base ai quali pianificare la gestione del paziente. Se in molti casi i pazienti affetti da NEN hanno una prognosi molto buona e necessitano di un follow-up post-chirurgico di tipo conservativo, in alcuni casi è necessario mettere in campo terapie aggressive e strategie terapeutiche innovative per cercare di garantire al paziente la migliore sopravvivenza. Molte caratteristiche tumorali (sede, dimensioni, indici proliferativi, attività ormonale, captazione di radiotraccianti) sono attualmente utilizzate per valutare la sopravvivenza dei pazienti con NEN, ma la loro accuratezza è ancora limitata. In questa rassegna vengono illustrati nuovi possibili marcatori prognostici, sia di tipo clinico che di laboratorio, che potrebbero nel prossimo futuro migliorare la valutazione dei pazienti con NEN, risparmiando i pazienti affetti da forme indolenti da strategie terapeutiche molto aggressive che andranno, al contrario, offerte da subito a pazienti con forme più aggressive. Questo approccio può consentire di risparmiare risorse sanitarie e, soprattutto, dare migliori risposte ai bisogni del paziente.

Obiettivi: i) Stratificare in maniera non invasiva le neoplasie del pancreas sulla base di comportamento biologico e prognosi, e ii) identificare marcatori imaging in grado di garantire una valutazione precoce dell’efficacia di trattamenti neoadiuvanti per PDAC e tumori dell’esofago. Metodi: Preliminarmente, abbiamo implementato una workflow comune per l’estrazione di features radiomiche usando i) metodi per garantire robustezza nonostante possibili differenze tra osservatori e ii) un processo tipo machine learning basato sul bootstrap. #1 – Una coorte retrospettiva di pazienti (pz) PDAC sottoposti a chirurgia diretta, arruolata per sviluppare un modello preoperatorio in grado di predire il rischio di ripresa precoce di malattia (<11 mesi). #2 – Una coorte prospettica di pz IPMN candidati a chirurgia, arruolata per identificare marcatori radiologici in grado di distinguere tra IPMN a basso/alto rischio. #3 – Una coorte retrospettiva di pz panNEN resecati, arruolata per costruire e validare modelli radiomici in grado di predire caratteristiche di aggressività biologica. #4 – Una coorte retrospettiva di pz PDAC sottoposta a chirurgia dopo nCT, arruola per sviluppare tre set di modelli basati su radiomica a) pre-/ b) post-nCT e c) ∆ in grado di predire il rischio di ripresa di malattia, uno status linfonodale N2 e la risposta patologica a nCT. #5 – Una coorte prospettica di pz con tumore dell’esofago candidati a nCRT. Ciascun paziente ha eseguito PET/MR prima, durante e dopo nCRT, calcolando l’ERI. TRG=1 significa risposta completa. Risultati: Modelli composti da variabili radiomiche e clinicoradiologiche si sono dimostrati efficaci nello stratificare il rischio di ripresa precoce di malattia per PDAC e nell’identificare caratteristiche di aggressività biologica di panNEN. La radiomica ∆ stratifica bene il rischio di ripresa di malattia (PDAC) dopo nCT. Per quanto riguarda i risultati non radiomici, abbiamo osservato un contenuto adiposo del pancreas maggiore nei pz IPMN con displasia severa/carcinoma invasivo. In riferimento al gruppo #5, pz con TRG=1 avevano valori di ERI significativamente più bassi di quelli con TRG≥2; gli stessi pazienti avevano anche un precoce incremento dell’ADC (alla valutazione intermedia). Conclusioni: I nostri risultati potrebbero integrare l’attuale algoritmo diagnostico e migliorare di conseguenza l’iter terapeutico dei pz con neoplasia di pancreas/esofago.
Aims: i) To non-invasively stratify pancreatic neoplasms based on their biological behaviour and prognosis, and ii) to identify imaging markers for early assessment of neoadjuvant treatment response for PDAC and oesophageal cancers. Methods: Five observational studies were designed. Preliminarily, a common radiomic workflow was defined using i) minimum redundancy, ii) robustness against delineation uncertainty and iii) a machine learning bootstrap-based method. #1 – A retrospective set of PDAC patients (pts) who underwent upfront surgery was enrolled to develop a preoperative model to stratify the chance of early (<11 months) distant disease relapse. #2 – A prospective set of IPMN pts candidate for resection was enrolled to identify radiological marker(s) to distinguish low- vs. high-risk IPMN. Besides high-risk stigmata/worrisome features, pancreatic fat content was assessed. #3 – A retrospective set of resected panNEN pts was enrolled to train and validate radiomic models to predict pathological characteristics of aggressiveness. #4 – A retrospective set of PDAC pts who underwent surgery after nCT was enrolled to develop three clusters of models based on a) pre-/ b) post-nCT and c) ∆ radiomics to predict disease recurrence after surgery, N2 and pathological response to nCT. #5 – A prospective set of oesophageal cancer pts scheduled to nCRT was enrolled. PET/MR was performed prior to, during and after treatment; for each patient, ERI was computed. TRG=1 stands for complete response. Results: Models comprising radiomic features and clinicoradiological variables were effective in stratifying the risk of early distant relapse after upfront surgery for PDAC, as well as pathological characteristics of panNEN aggressiveness. ∆ radiomics well stratifies the risk of relapse after nCT for PDAC. Non-radiomic findings were also intriguing. Pancreatic fat content was higher in IPMN pts with high-grade dysplasia/invasive carcinoma than in low/moderate-grade dysplasia. When dealing with cohort#5, pts with TRG=1 had significantly lower ERI values than those with TRG≥2; they also had a significant higher median increase in tumour ADC from baseline to intermediate scans. Conclusions: Our findings could complement current diagnostic workflow and improve clinical decision-making for pts with pancreatic/esophageal neoplasms.

Gliomas are the most common primary brain tumours. Despite advances in surgical techniques, postoperative supportive care, radiation and adjuvant systemic therapy, the life expectancy of patients with high grade glioma has remained essentially poor. Furthermore differential diagnosis among astrocytomas, oligodendrogliomas and oligoastrocytomas is very challenging and subject to inter-observer variability. The purpose of the research was: 1) to investigate a series of high grade and low grade gliomas at gene and protein (immunohistochemistry) levels to disclose possible genetic portraits of malignancy; 2) to verify the utility of Nogo-A, Olig-2 and synaptophysin in providing a correct histological diagnosis of oligodendroglioma and to investigate a possible complementary role in selecting the best areas suitable for detecting 1p/19q codeletion using FISH analysis; 3) to study the role of microRNA in high grade gliomas. In order to obtain these goals large series of brain tumors were studied with DNA microarrays, immunohistochemistry and RT-PCR The results demonstrated that: - Overexpression of IGFBP-2 and CDC20 is highly related to glioblastomas and their immunopositivity can be useful for the identification of glioblastoma in small biopsies. - Nogo-A is the most useful and specific marker in differentiating oigodendrogliomas from other gliomas. Furthermore, using a Nogo-A driven FISH analysis, it is possible to identify a larger number of 1p19q codeletions in gliomas. - microRNAs can be studied in paraffin embedded tissues better than in fresh tissues. A series of six microRNA, significatively deregulated in glioblastomas, may represent a genetic signature with prognostic and predictive value and could constitute candidates for novel anti-cancer therapeutics.

Gliomas are the most common primary brain tumours. Despite advances in surgical techniques, postoperative supportive care, radiation and adjuvant systemic therapy, the life expectancy of patients with high grade glioma has remained essentially poor. Furthermore differential diagnosis among astrocytomas, oligodendrogliomas and oligoastrocytomas is very challenging and subject to inter-observer variability. The purpose of the research was: 1) to investigate a series of high grade and low grade gliomas at gene and protein (immunohistochemistry) levels to disclose possible genetic portraits of malignancy; 2) to verify the utility of Nogo-A, Olig-2 and synaptophysin in providing a correct histological diagnosis of oligodendroglioma and to investigate a possible complementary role in selecting the best areas suitable for detecting 1p/19q codeletion using FISH analysis; 3) to study the role of microRNA in high grade gliomas. In order to obtain these goals large series of brain tumors were studied with DNA microarrays, immunohistochemistry and RT-PCR The results demonstrated that: - Overexpression of IGFBP-2 and CDC20 is highly related to glioblastomas and their immunopositivity can be useful for the identification of glioblastoma in small biopsies. - Nogo-A is the most useful and specific marker in differentiating oigodendrogliomas from other gliomas. Furthermore, using a Nogo-A driven FISH analysis, it is possible to identify a larger number of 1p19q codeletions in gliomas. - microRNAs can be studied in paraffin embedded tissues better than in fresh tissues. A series of six microRNA, significatively deregulated in glioblastomas, may represent a genetic signature with prognostic and predictive value and could constitute candidates for novel anti-cancer therapeutics.

Background: MPLC represents a diagnostic challenge. Topic of the discussion is how to distinguish these patients as a metastatic or a multifocal disease. While in case of the different histology there are less doubt on the opposite in case of same histology is mandatory to investigate on other clinical features to rule out this question. Matherials and Methods: A retrospective review identified all patients treated surgically for a presumed diagnosis of SPLC. Pre-operative staging was obtained with Total CT scan and fluoro-deoxy positron emission tomography and mediastinoscopy. Patients with nodes interest or extra-thoracic location were excluded from this study. Epidermal growth factor receptor (EGFR) expression with complete immunohistochemical analisis was evaluated. Survival was estimated using Kaplan-Meyer method, and clinical features were estimated using a long-rank test or Cox proportional hazards model for categorical and continuous variable, respectively. Results: According to American College Chest Physician, 18 patients underwent to surgical resection for a diagnosis of MPLC. Of these, 8 patients had 3 or more nodules while 10 patients had less than 3 nodules. Pathologic examination demonstrated that 13/18(70%) of patients with multiple histological types was Adenocarcinoma, 2/18(10%) Squamous carcinoma, 2/18(10%) large cell carcinoma and 1/18(5%) Adenosquamosu carcinoma. Expression of EGFR has been evaluated in all nodules: in 7 patients of 18 (38%) the percentage of expression of each nodule resulted different. Conclusions: MPLC represent a multifocal disease where interactions of clinical informations with biological studies reinforce the diagnosis. EGFR could contribute to differentiate the nodules. However, further researches are necessary to validate this hypothesis.

Background: MPLC represents a diagnostic challenge. Topic of the discussion is how to distinguish these patients as a metastatic or a multifocal disease. While in case of the different histology there are less doubt on the opposite in case of same histology is mandatory to investigate on other clinical features to rule out this question. Matherials and Methods: A retrospective review identified all patients treated surgically for a presumed diagnosis of SPLC. Pre-operative staging was obtained with Total CT scan and fluoro-deoxy positron emission tomography and mediastinoscopy. Patients with nodes interest or extra-thoracic location were excluded from this study. Epidermal growth factor receptor (EGFR) expression with complete immunohistochemical analisis was evaluated. Survival was estimated using Kaplan-Meyer method, and clinical features were estimated using a long-rank test or Cox proportional hazards model for categorical and continuous variable, respectively. Results: According to American College Chest Physician, 18 patients underwent to surgical resection for a diagnosis of MPLC. Of these, 8 patients had 3 or more nodules while 10 patients had less than 3 nodules. Pathologic examination demonstrated that 13/18(70%) of patients with multiple histological types was Adenocarcinoma, 2/18(10%) Squamous carcinoma, 2/18(10%) large cell carcinoma and 1/18(5%) Adenosquamosu carcinoma. Expression of EGFR has been evaluated in all nodules: in 7 patients of 18 (38%) the percentage of expression of each nodule resulted different. Conclusions: MPLC represent a multifocal disease where interactions of clinical informations with biological studies reinforce the diagnosis. EGFR could contribute to differentiate the nodules. However, further researches are necessary to validate this hypothesis.