Cancer Science & Therapy

Radiotherapy has been the mainstay of the treatment of stage III non-small cell lung cancer (NSCLC) patients. In the early nineties, combined treatment with chemotherapy was introduced. In 1995, a meta-analysis showed improved treatment outcome of the sequential use of cisplatin-based chemotherapy and radiotherapy (RCT) compared to radiotherapy alone. Subsequent randomized studies and the two meta-analyses demonstrated that concurrent radiochemotherapy (RCT) is superior (local control and overall survival) to sequential used both method. However, several questions remain unanswered concerning the optimal chemotherapy regimen and radiotherapy doses and techniques in terms of treatment outcome and toxicity profile. Targeted therapies represent a new class of drugs which interfere with specific molecular targets (typically proteins) playing critical roles in tumor growth and progression. Some combinations appear to be too toxic like the vascular epithelial growth factor antibody bevacizumab. The feasibility of adding the epidermal growth factor receptor inhibitor cetuximab has been recently reported for NSCLC patients. Strategies to safely incorporate novel antiangiogenic agents into combined-modality therapy in lung cancer are needed. The rapid development of molecular oncology will hopefully contribute to a better patient selection to particular strategies and to treatment optimization. Increasing radiotherapy doses applied according to up-to-date techniques and combinations with new biologicals might lead to further treatment improvements.

Lung cancer is one of the most common causes of cancer-related death in men and women throughout the world. An appropriate statistical model for survival analysis on lung cancer can provide precise prognosis for treatment planning. Usually the traditional prognostic decisions are made purely based on pathologists’ subjective evaluations. It has been proven that accuracy and objectivity of diagnosis and prognosis, when assisted with computational algorithm, will dramatically increase. In this paper, we have developed a novel prediction model called LC-Morph. The prediction model includes cell detection, segmentation, and statistical model for survival analysis. 122 lung cancer patients’ images extracted from the cancer genome atlas (TCGA) data set has been used in this study. A robust seed detection-based cell segmentation algorithm is proposed to accurately segment each individual cell in the image. Based on the cell segmentation results, a set of comprehensive cellular features are extracted using some efficient image feature descriptors. To build a prognostic image signature for patient overall survival, the study data set is randomly split into a training data set (82 patients) and a testing data set (40 patients). Based on the training data, univariate Cox models are used to identify informative image features. A lasso-penalized Cox model is used to derive an image feature-based prognostic model and calculate the corresponding risk score (LC-Morph score) which is used to evaluate the patient’s survival. This prediction score is externally validated using the testing data set. We also stratify patients into high- and low-risk groups based on the LC-Morph score and find significantly longer survival time in the low-risk group than the high-risk group (log-rank P=0.013), which indicates the efficacy of the LC-Morph score in estimating the survival rates of lung cancer patients.

Background and objectives: Management of patients with breast cancer often fails because of inherent or acquired resistance to chemotherapy. BRUCE (BIR repeat containing ubiquitin-conjugating enzyme) is a member of the inhibitor of apoptosis protein (IAP) family. It has various cellular functions including suppression of apoptosis and promotion of cytokinesis. Furthermore, it pays a critical role in promotion of DNA damage repair and preservation of genome stability, a new function recently reported by our group. Although BRUCE is expressed in breast cancer cell lines, its expression in human primary breast tumors and its contribution to chemoresistance in breast cancers has not been explored. Chemotherapeutic drugs are used in the treatment of breast cancer patients. However, they are not effective to all patients and patients often develop resistance. Consequently we explored if BRUCE protein level, as judged by immunohistochemistry (IHC), is higher in primary breast tumors than normal breast tissue. We also examined if depletion of BRUCE, using a lentiviral shRNA approach, enhances cell sensitivity to multiple chemotherapeutic agents, including cisplatin, an agent that induces DNA damage by generating DNA cross-links, and taxol, a microtubule stabilizer and mitotic inhibitor. The reason for including these two chemotherapeutic agents in this study is that they hit two essential cellular processes of DNA repair and cytokinesis in which BRUCE plays critical roles.

Results and methods: IHC analysis of BRUCE revealed significantly higher levels of BRUCE in primary breast tumors than normal breast tissue. Knockdown of BRUCE protein expression by lentiviral shRNA resulted in increased sensitivity to cisplatin in the resistant breast cancer MDB-MD-231 cell line. Moreover, depletion of BRUCE in this cell line achieved a more profound level of cell killing when coupled to low doses of cisplatin and taxol combined, rather than either drug used alone.

Conclusions: Our data suggest that elevated protein levels of BRUCE in breast tumors may contribute to chemoresistance in breast cancer patients. In support of this suggestion, our data demonstrate that a reduction in BRUCE expression in breast cancer cell lines increases the toxicity of several chemotherapeutic agents. In all likelihood, the contribution of increased BRUCE levels to chemoresistance are likely due to its roles in suppression of apoptosis, promotion of cytokinesis and facilitation of DNA damage repair. These observations suggest that therapeutic suppression of BRUCE could improve chemosensitivity in chemo-resistant breast cancer patients. Therefore, future development of effective inhibitors of BRUCE could benefit patients with high BRUCE expression and chemoresistance.

Aim: The aim of this study was to evaluate the clinicopathological features and prognosis of gastric Signet Ring Cell Carcinoma (SRCC) including measurement of tumor markers (CEA, CA 19-9) and CRP.

Material and method: There were 19 patients with histopathological diagnosis of signet ring cell carcinoma of the stomach. Clinicopathological parameters, including gender and age of the patients, duration of symptoms, size and location of tumors, depth of invasion (T stage), lymph node metastasis status (N stage), distant metastasis (M status) and operative details, were collected retrospectively. CEA, CA 19-9 and CRP levels were measured in all patients.

Results: The mean age of the patients was 63.74 ± 15.07 (range 37-90 years). Median survival time was 17.4 ± 10.7 month (range 4-48 months). The mean CA 19-9 level was 14.4 ± 23.1 (0.8-101.6), CEA level was 91.9 ± 227.2 (0.46-989) and CRP level was 1.79 ± 1.19 (0.3-3.7). Sixteen patients were classified as stage III or IV disease. Five patients were operated with total gastrectomy and 9 patients with gastroenterostomy due to unresectable tumor.

Conclusion: Clinicopathological behavior of gastric SRCC is still debated. In this serial, most of the patients with gastric SRCC were diagnosed and treated in last stages of their diseases. Although CA 19-9 and CEA levels were inceased in some patients with SRCC, diagnostic value of these markers is debated.Another marker CRP was found normal in most of the patients with gastric SRCC in this serial.

Objectives: Prostate Cancer (PCa) and Benign Prostatic Hyperplasia (BPH) are frequently coexisting in elderly men. The measurement of serum PSA together with Digital Rectal Examination (DRE) represents the primary diagnostic tool to suspect PCa, whereas definitive diagnosis is achieved by prostate biopsy. The low specificity of PSA and the modest detection rate of biopsy convict the patient to a quite often unnecessary and uncomfortable clinical itinerary. There is a urgent need for new and more accurate methodologies to diagnosize PCa. In the present study, the expression of 4 mRNAs and 2 miRNAs was evaluated in post DRE urine cell pellets from patients suffering PCa and age-matched subjects affected by BPH with elevated PSA levels. We also evaluated the diagnostic accuracy of markers in predicting PCa.

Materials and methods: The expression levels of 4 mRNAs (3 kallikreins - KLK3, KLK11, KLK13 and a prostate cancer antigen - PCA3) and 2 microRNAs (miR-9-3p and miR-19a-3p) were assayed by means of real-time PCR in post DRE urine of 79 men undergoing prostate biopsy for PSA levels > 3 ng/mL. The diagnostic power of tested markers was evaluated through logistic regression analysis.

Results: PCA3 was undetectable in 22 out of 38 BPH subjects. KLK3 and KLK11 were significantly upregulated in PCa group (p value < 0.001), while miR-9-3p and miR-19a-3p were up-regulated in BPH group (p value <0.001 and < 0.01, respectively). KLK13 was not differentially expressed between groups. MiR-19a-3p and miR- 9-3p reached the highest specificity (64.29%) and sensitivity (81.08%), respectively. The more accurate bivariate logistic model was obtained combining KLK11 with either miR-9-3p and miR-19a-3p.

Conclusions: Our findings demonstrated that selected kallikreins and miRNAs proved to be an accurate diagnostic tool for PCa. Urine cells pellets obtained after DRE represent a reliable biological matrix for minimally invasive gene expression assays.