Maria Cristina Montesco

A gene expression signature associated with survival in metastatic melanoma

BackgroundCurrent clinical and histopathological criteria used to define the prognosis of melanoma patients are inadequate for accurate prediction of clinical outcome. We investigated whether genome screening by means of high-throughput gene microarray might provide clinically useful information on patient survival.MethodsForty-three tumor tissues from 38 patients with stage III and stage IV melanoma were profiled with a 17,500 element cDNA microarray. Expression data were analyzed using significance analysis of microarrays (SAM) to identify genes associated with patient survival, and supervised principal components (SPC) to determine survival prediction.ResultsSAM analysis revealed a set of 80 probes, corresponding to 70 genes, associated with survival, i.e. 45 probes characterizing longer and 35 shorter survival times, respectively. These transcripts were included in a survival prediction model designed using SPC and cross-validation which allowed identifying 30 predicting probes out of the 80 associated with survival.ConclusionThe longer-survival group of genes included those expressed in immune cells, both innate and acquired, confirming the interplay between immunological mechanisms and the natural history of melanoma. Genes linked to immune cells were totally lacking in the poor-survival group, which was instead associated with a number of genes related to highly proliferative and invasive tumor cells.

Early (Sentinel Lymph Node Biopsy-Guided) Versus Delayed Lymphadenectomy in Melanoma Patients With Lymph Node Metastases: Personal Experience and Literature Meta-Analysis

It is debated whether patients with melanoma who undergo lymphadenectomy after a positive sentinel lymph node (SN) biopsy (SNB) have a better prognosis compared with patients who are treated for clinically evident disease.

Impact of molecular analysis on the final sarcoma diagnosis: a study on 763 cases collected during a European epidemiological study.

Sarcomas are rare, heterogenous, and often difficult to classify. A large proportion of sarcomas are associated with specific molecular genetic lesions such as translocations, mutations, and amplifications, which are helpful in the diagnosis of individual cases. However, the exact impact of molecular genetics on the final diagnosis of sarcomas is unknown. In this study, all soft tissue and visceral sarcomas arising in patients living in 3 European regions in 2 countries (representing 13 million inhabitants) were collected and reviewed during 2 consecutive years. A molecular analysis was performed for all suspicions of sarcomas with specific genetic lesions [mutations of KIT/PDGFRA in gastrointestinal stromal tumors (GISTs), reciprocal translocation, or amplification of MDM2 in atypical lipomatous tumors, well-differentiated liposarcoma-dedifferentiated liposarcoma (ALT/WDLPS-DDLPS)]. To evaluate the impact of molecular tests, a premolecular analysis diagnosis was proposed with 3 categories of certainty: certain, probable, or possible. A molecular analysis was performed in 763/1484 tumors corresponding to 295 cases in which GIST was suspected, 248 sarcomas with a suspicion of translocation, and 220 cases in which ALT/WDLPS-DDLPS was suspected. Molecular analysis was found to be useful (confirms a probable diagnosis) in 11 (4%) GISTs, 62 (26%) suspicions of translocation, and 66 (31%) suspicions of ALT/WDLPS-DDLPS; and necessary (allows a possible diagnosis) in 2 (<1%) GISTs, 31 (12%) suspicions of translocation, and 19 (9%) suspicions of ALT/WDLPS-DDLPS. This study performed in an epidemiological setting demonstrates the significant impact of molecular analysis on the final sarcoma diagnosis and favors such an analysis on any tumor with a suspicion of a specific genomic abnormality and for which the diagnosis is uncertain.

Histological evaluation of thyroid carcinomas: reproducibility of the "WHO" classification.

Aims and Backgrounds Thyroid carcinomas display several pathologic features, show different behavior and necessitate different treatment; thus correct classification is mandatory. Methods The kappa statistic was used as a measure of agreement in a panel of seven pathologists who reviewed 200 cases of thyroid tumors. Results Overall agreement was 83 % (k = 68). Good agreement was found for anaplastic (k = 0.85) and papillary carcinomas (k = 0.81); agreement for medullary carcinoma was acceptable (k = 0.80), suboptimal for other (k = 0.67), and poor for follicular carcinoma (k = 0.54). Conclusions Central pathology review of thyroid carcinomas is recommended when clinical and epidemiologic trials are planned.

Gastrointestinal stromal tumors: Report of an audit and review of the literature

Gastrointestinal stromal tumors (GISTs), tumors characterized by c-KIT mutations, are the most frequent mesenchymal tumors of the digestive tract. The stomach is the most commonly involved site. Localization, size and mitotic rate are reliable predictors of survival and the two milestones of GISTs treatment are surgery and imatinib. This article is aimed to report the data of an audit, carried out on the morphological and clinical aspects of the disease and to review the present knowledge on GISTs. A total of 172 patients with GISTs (M : F=1 : 1; mean age 65 years) were recruited. The stomach was the most frequently involved site. In 50% of the cases the tumor was smaller than 5 cm, whereas major symptoms were observed in 43% of the cases. Predictors of progressive disease were present only in a small percentage of cases but the disease was in the metastatic phase in over 25% of the cases at diagnosis. Familial aggregation was rare but a consistent share of the patients (21%) had other synchronous or metachronous cancers. The most frequent mutations were in-frame deletions and point mutations of c-KIT exon 11. This report confirms in part the available data on GIST in a consecutive series of patients recruited in Italy and shows that only large collaborative multicenter studies provide data sound enough to enable making reasonable clinical and therapeutic choices, and suggests that, as a measure of secondary prevention, a diagnostic definition should be obtained in all submucosal lesions of the GI tract and that GIST patients should be screened for second tumors.

Adherence to treatment guidelines for primary sarcomas affects patient survival: a side study of the European CONnective TIssue CAncer NETwork (CONTICANET)

BACKGROUND The impact of adherence to clinical practice guidelines (CPGs) for loco-regional treatment (i.e. surgery and radiotherapy) and chemotherapy on local disease control and survival in sarcoma patients was investigated in a European study conducted in an Italian region (Veneto). PATIENTS AND METHODS The completeness of the adherence to the Italian CPGs for sarcomas treatment was assessed by comparing the patients charts and the CPGs. Propensity score-adjusted multivariate survival analysis was used to assess the impact of CPGs adherence on patient clinical outcomes. RESULTS A total of 151 patients were included. Adherence to CPGs for loco-regional therapy and chemotherapy was observed in 106 out of 147 (70.2%) and 129 out of 139 (85.4%) patients, respectively. Non-adherence to CPGs for loco-regional treatment was independently associated with AJCC stage III disease [odds ratio (OR) 1.77, P = 0.011] and tumor-positive excision margin (OR 3.55, P = 0.003). Patients not treated according to the CPGs were at a higher risk of local recurrence [hazard ratio (HR) 5.4, P < 0.001] and had a shorter sarcoma-specific survival (HR 4.05, P < 0.001), independently of tumor stage. CONCLUSIONS Incomplete adherence to CPGs for loco-regional treatment of sarcomas was associated with worse prognosis in patients with non-metastatic tumors.

Early detection of melanoma: an educational campaign in Padova, Italy.

&NA; To evaluate a public campaign for the early referral and treatment of cutaneous melanoma, an educational programme based on self‐selection by subjects was organized in Padova, Italy in 1991. In the period from 1991 to 1996, 90,000 leaflets containing information on naevi, melanoma and skin self‐examination were mailed to each household, reaching a population of 243,000 subjects. A total of 2050 individuals requested a skin check as a result of the leaflet. Most were at low risk, the majority being female (68%) and aged under 40 years (51.6%), with no risk factors (58.3%). One hundred and ninety subjects were referred for surgery for pigmented and non‐pigmented suspect lesions. Histological diagnoses, obtained for all lesions, comprised 13 melanomas, 17 dysplastic naevi, 17 basocellular carcinomas, 140 pigmented benign lesions and three lesions of other types. The percentage of thin melanomas (< 1.50 mm) was 92.3%. Three hundred and fifty patients considered at risk at the first skin examination attended regular follow‐up examinations. The sensitivity and predictive positive value of the visual examination were 92.8% and 6.8%, respectively. The impact of this campaign was evaluated in the Local Health District of Padova, comparing data from the pre‐campaign period (1987 1990) with those from the campaign period (1991 1996); a trend towards a lower stage was observed (mean thickness 2.0 mm versus 1.50 mm; P < 0.02).

Sentinel node status prediction by four statistical models: results from a large bi-institutional series (n = 1132).

Objective:To improve selection for sentinel node (SN) biopsy (SNB) in patients with cutaneous melanoma using statistical models predicting SN status. Summary Background Data:About 80% of patients currently undergoing SNB are node negative. In the absence of conclusive evidence of a SNB-associated survival benefit, these patients may be over-treated. Here, we tested the efficiency of 4 different models in predicting SN status. Methods:The clinicopathologic data (age, gender, tumor thickness, Clark level, regression, ulceration, histologic subtype, and mitotic index) of 1132 melanoma patients who had undergone SNB at institutions in Italy and Australia were analyzed. Logistic regression, classification tree, random forest, and support vector machine models were fitted to the data. The predictive models were built with the aim of maximizing the negative predictive value (NPV) and reducing the rate of SNB procedures though minimizing the error rate. Results:After cross-validation logistic regression, classification tree, random forest, and support vector machine predictive models obtained clinically relevant NPV (93.6%, 94.0%, 97.1%, and 93.0%, respectively), SNB reduction (27.5%, 29.8%, 18.2%, and 30.1%, respectively), and error rates (1.8%, 1.8%, 0.5%, and 2.1%, respectively). Discussion:Using commonly available clinicopathologic variables, predictive models can preoperatively identify a proportion of patients (∼25%) who might be spared SNB, with an acceptable (1%–2%) error. If validated in large prospective series, these models might be implemented in the clinical setting for improved patient selection, which ultimately would lead to better quality of life for patients and optimization of resource allocation for the health care system.

Support vector machine learning model for the prediction of sentinel node status in patients with cutaneous melanoma.

Background:Currently, approximately 80% of melanoma patients undergoing sentinel node biopsy (SNB) have negative sentinel lymph nodes (SLNs), and no prediction system is reliable enough to be implemented in the clinical setting to reduce the number of SNB procedures. In this study, the predictive power of support vector machine (SVM)-based statistical analysis was tested.Methods:The clinical records of 246 patients who underwent SNB at our institution were used for this analysis. The following clinicopathologic variables were considered: the patient’s age and sex and the tumor’s histological subtype, Breslow thickness, Clark level, ulceration, mitotic index, lymphocyte infiltration, regression, angiolymphatic invasion, microsatellitosis, and growth phase. The results of SVM-based prediction of SLN status were compared with those achieved with logistic regression.Results:The SLN positivity rate was 22% (52 of 234). When the accuracy was ≥80%, the negative predictive value, positive predictive value, specificity, and sensitivity were 98%, 54%, 94%, and 77% and 82%, 41%, 69%, and 93% by using SVM and logistic regression, respectively. Moreover, SVM and logistic regression were associated with a diagnostic error and an SNB percentage reduction of (1) 1% and 60% and (2) 15% and 73%, respectively.Conclusions:The results from this pilot study suggest that SVM-based prediction of SLN status might be evaluated as a prognostic method to avoid the SNB procedure in 60% of patients currently eligible, with a very low error rate. If validated in larger series, this strategy would lead to obvious advantages in terms of both patient quality of life and costs for the health care system.

Proliferating cell nuclear antigen (PCNA) and recurrence in patients with cutaneous melanoma

A positive correlation between PCNA and the most important histoprognostic factors of cutaneous melanoma has been demonstrated. The aim of our work was to evaluate the efficacy of PCNA in predicting melanoma recurrence and to compare it with that of Breslow thickness. One-hundred and fifteen patients (75 women, 40 men; mean age 50 years) with primary cutaneous melanoma were retrieved. pTNM stages were as follows: stage I, 54 patients; stage II, 31 patients; stage III, 26 patients; and stage IV, four patients. The mean follow-up period was 55 months (range 2-260). Six patients developed lymph node metastases and 28 developed distant metastases; 27 patients died within 2-202 months from diagnosis. Tumour thickness was re-evaluated for each case. PCNA immunostaining was performed using the avidin-biotin complex method and the percentage of PCNA-positive tumour cells was indicated as the PCNA index. In order to evaluate and compare the PCNA index and Breslow thickness as predictors of recurrence, the receiver-operating characteristic (ROC) curve method, based on true-positive and false-positive rates was used. The PCNA index showed the highest true-positive rates and the lowest false-positive rates in the 5-30 interval. The PCNA index optimal cut-off is 20, characterized by 70% sensitivity and 80% specificity; Breslow thickness optimal cutoff is 3.5 mm, with 40% sensitivity and 90% specificity. Our results indicate that the PCNA index has a higher efficacy in predicting locoregional and distant recurrences in patients presenting primary cutaneous melanoma.