Comparing the performance of visual estimation and standard uptake value of F-18 fluorodeoxyglucose positron emission tomography/computed tomography for detecting malignancy in pancreatic tumors other than invasive ductal carcinoma

Development and verification of a personalized immune prognostic feature in breast cancer

IMPACT STATEMENT

Breast cancer is among the highest prevalent malignant tumors worldwide with a low survival ratio. Immune-related genes have great potential as prognostic indicator in many types of tumors. Therefore, we have attempted to develop immune-related gene markers to enhance the prognosis of breast cancer. 17-IRGPs signature was constructed as a newly developed prognostic indicator to predict the survival of BC patients.

Clinical Imaging Technology and the Diagnosis in Patient-centered Interdisciplinary Care

Clinical imaging examinations and the diagnosis of their findings play an important role in patientcentered interdisciplinary care. Clinical imaging tests, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI) and nuclear medicine scans, are performed both in the initial diagnosis to identify the disease and at follow-up with the radiology team. Imaging technology is advancing day by day, both the hardware and software. CT and MRI are useful for confirming the size and location of lesions, providing what is known as morphologic images. CT can perform whole-body imaging very quickly, and the huge data are reconstructed in many ways with advanced computer systems. Three-dimensional CT, such as virtual colonography and bronchography, isuseful for planning the approach before surgery or endoscopic study. MRI isuseful for detecting acute cerebral infarction and evaluating brain perfusion or brain metabolites using MR spectroscopy. Fluorodeoxyglucose-positron emission tomography (FDG-PET)/CT is a molecular imaging modality mainly used in oncology for the initial diagnosis, staging and detection of recurrence or metastasis after treatment as well as the evaluation of the treatment response. The focus of this paper was to elucidate the typesand use of clinical imaging technologies, with a focus on CT, MRI and FDG-PET. J. Med.I nvest. 66:31-34, February, 2019.

Imaging modalities for characterising focal pancreatic lesions

BACKGROUND

Increasing numbers of incidental pancreatic lesions are being detected each year. Accurate characterisation of pancreatic lesions into benign, precancerous, and cancer masses is crucial in deciding whether to use treatment or surveillance. Distinguishing benign lesions from precancerous and cancerous lesions can prevent patients from undergoing unnecessary major surgery. Despite the importance of accurately classifying pancreatic lesions, there is no clear algorithm for management of focal pancreatic lesions.

OBJECTIVES

To determine and compare the diagnostic accuracy of various imaging modalities in detecting cancerous and precancerous lesions in people with focal pancreatic lesions.

SEARCH METHODS

We searched the CENTRAL, MEDLINE, Embase, and Science Citation Index until 19 July 2016. We searched the references of included studies to identify further studies. We did not restrict studies based on language or publication status, or whether data were collected prospectively or retrospectively.

SELECTION CRITERIA

We planned to include studies reporting cross-sectional information on the index test (CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), EUS (endoscopic ultrasound), EUS elastography, and EUS-guided biopsy or FNA (fine-needle aspiration)) and reference standard (confirmation of the nature of the lesion was obtained by histopathological examination of the entire lesion by surgical excision, or histopathological examination for confirmation of precancer or cancer by biopsy and clinical follow-up of at least six months in people with negative index tests) in people with pancreatic lesions irrespective of language or publication status or whether the data were collected prospectively or retrospectively.

DATA COLLECTION AND ANALYSIS

Two review authors independently searched the references to identify relevant studies and extracted the data. We planned to use the bivariate analysis to calculate the summary sensitivity and specificity with their 95% confidence intervals and the hierarchical summary receiver operating characteristic (HSROC) to compare the tests and assess heterogeneity, but used simpler models (such as univariate random-effects model and univariate fixed-effect model) for combining studies when appropriate because of the sparse data. We were unable to compare the diagnostic performance of the tests using formal statistical methods because of sparse data.

MAIN RESULTS

We included 54 studies involving a total of 3,196 participants evaluating the diagnostic accuracy of various index tests. In these 54 studies, eight different target conditions were identified with different final diagnoses constituting benign, precancerous, and cancerous lesions. None of the studies was of high methodological quality. None of the comparisons in which single studies were included was of sufficiently high methodological quality to warrant highlighting of the results. For differentiation of cancerous lesions from benign or precancerous lesions, we identified only one study per index test. The second analysis, of studies differentiating cancerous versus benign lesions, provided three tests in which meta-analysis could be performed. The sensitivities and specificities for diagnosing cancer were: EUS-FNA: sensitivity 0.79 (95% confidence interval (CI) 0.07 to 1.00), specificity 1.00 (95% CI 0.91 to 1.00); EUS: sensitivity 0.95 (95% CI 0.84 to 0.99), specificity 0.53 (95% CI 0.31 to 0.74); PET: sensitivity 0.92 (95% CI 0.80 to 0.97), specificity 0.65 (95% CI 0.39 to 0.84). The third analysis, of studies differentiating precancerous or cancerous lesions from benign lesions, only provided one test (EUS-FNA) in which meta-analysis was performed. EUS-FNA had moderate sensitivity for diagnosing precancerous or cancerous lesions (sensitivity 0.73 (95% CI 0.01 to 1.00) and high specificity 0.94 (95% CI 0.15 to 1.00), the extremely wide confidence intervals reflecting the heterogeneity between the studies). The fourth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (dysplasia) provided three tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing invasive carcinoma were: CT: sensitivity 0.72 (95% CI 0.50 to 0.87), specificity 0.92 (95% CI 0.81 to 0.97); EUS: sensitivity 0.78 (95% CI 0.44 to 0.94), specificity 0.91 (95% CI 0.61 to 0.98); EUS-FNA: sensitivity 0.66 (95% CI 0.03 to 0.99), specificity 0.92 (95% CI 0.73 to 0.98). The fifth analysis, of studies differentiating cancerous (high-grade dysplasia or invasive carcinoma) versus precancerous (low- or intermediate-grade dysplasia) provided six tests in which meta-analysis was performed. The sensitivities and specificities for diagnosing cancer (high-grade dysplasia or invasive carcinoma) were: CT: sensitivity 0.87 (95% CI 0.00 to 1.00), specificity 0.96 (95% CI 0.00 to 1.00); EUS: sensitivity 0.86 (95% CI 0.74 to 0.92), specificity 0.91 (95% CI 0.83 to 0.96); EUS-FNA: sensitivity 0.47 (95% CI 0.24 to 0.70), specificity 0.91 (95% CI 0.32 to 1.00); EUS-FNA carcinoembryonic antigen 200 ng/mL: sensitivity 0.58 (95% CI 0.28 to 0.83), specificity 0.51 (95% CI 0.19 to 0.81); MRI: sensitivity 0.69 (95% CI 0.44 to 0.86), specificity 0.93 (95% CI 0.43 to 1.00); PET: sensitivity 0.90 (95% CI 0.79 to 0.96), specificity 0.94 (95% CI 0.81 to 0.99). The sixth analysis, of studies differentiating cancerous (invasive carcinoma) from precancerous (low-grade dysplasia) provided no tests in which meta-analysis was performed. The seventh analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) provided two tests in which meta-analysis was performed. The sensitivity and specificity for diagnosing cancer were: CT: sensitivity 0.83 (95% CI 0.68 to 0.92), specificity 0.83 (95% CI 0.64 to 0.93) and MRI: sensitivity 0.80 (95% CI 0.58 to 0.92), specificity 0.81 (95% CI 0.53 to 0.95), respectively. The eighth analysis, of studies differentiating precancerous or cancerous (intermediate- or high-grade dysplasia or invasive carcinoma) from precancerous (low-grade dysplasia) or benign lesions provided no test in which meta-analysis was performed.There were no major alterations in the subgroup analysis of cystic pancreatic focal lesions (42 studies; 2086 participants). None of the included studies evaluated EUS elastography or sequential testing.

AUTHORS' CONCLUSIONS

We were unable to arrive at any firm conclusions because of the differences in the way that study authors classified focal pancreatic lesions into cancerous, precancerous, and benign lesions; the inclusion of few studies with wide confidence intervals for each comparison; poor methodological quality in the studies; and heterogeneity in the estimates within comparisons.

Biomarker discovery to improve prediction of breast cancer survival: using gene expression profiling, meta-analysis, and tissue validation

Purpose

Breast cancer is the leading cause of cancer death worldwide in women. The molecular mechanism for human breast cancer is unknown. Gene microarray has been widely used in breast cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis survival. So far, the valuable multigene signatures in clinical practice are unclear, and the biological importance of individual genes is difficult to detect, as the described signatures virtually do not overlap. Early prognosis of this disease, breast invasive ductal carcinoma (IDC) and breast ductal carcinoma in situ (DCIS), is vital in breast surgery.

Methods

Thus, this study reports gene expression profiling in large breast cancer cohorts from Gene Expression Omnibus, including GSE29044 (N=138) and GSE10780 (N=185) test series and four independent validation series GSE21653 (N=266), GSE20685 (N=327), GSE26971 (N=276), and GSE12776 (N=204). Significantly differentially expressed genes in human breast IDC and breast DCIS were detected by transcriptome microarray analysis.

Results

We created a set of three genes (MAMDC2, TSHZ2, and CLDN11) that were significantly correlated with disease-free survival of breast cancer patients using a univariate Cox regression model (significance level P<0.01) in a meta-analysis. Based on the risk score of the three genes, the test series patients could be separated into low-risk and high-risk groups with significantly different survival times. This signature was validated in the other three cohorts. The prognostic value of this three-gene signature was confirmed in the internal validation series and another four independent breast cancer data sets. The prognostic impact of one of the three genes, CLDN11, was confirmed by immunohistochemistry. CLDN11 was significantly overexpressed in human breast IDC as compared with normal breast tissues and breast DCIS.

Conclusion

Using novel gene expression profiling together with a meta-analysis validation approach, we have identified a three-gene signature with independent prognostic impact. Furthermore, CLDN11 may offer a biomarker to predict prognosis as well as a new target for prognostic and therapeutic intervention for human breast IDC.