Soluble interleukin-6 receptor is a serum biomarker for the response of esophageal carcinoma to neoadjuvant chemoradiotherapy.

Preoperative chemoradiotherapy has been shown to improve the outcome of patients with esophageal cancer, but because response to this therapy varies, it is desirable to identify in advance individuals who would be unlikely to benefit, in order to avoid unnecessary adverse drug effects. The serum profiles of 84 cytokines and related proteins were determined in 37 patients with esophageal squamous cell carcinoma who received identical neoadjuvant preoperative chemoradiotherapy regimens and underwent surgical resection. Histological response to this therapy was assessed in surgically resected specimens. The serum soluble interleukin-6 receptor (sIL6R) level was significantly higher in 30 patients who failed to achieve a histological complete response (P = 0.005). Multivariate analysis revealed that the increased level of sIL6R was one of several significant independent predictors of an unfavorable outcome (hazard ratio, 2.87; P = 0.017). The increased level of this cytokine in patients who did not obtain a complete response was reproducibly observed in an independent cohort of 34 patients. Esophageal squamous cell carcinoma patients with an increased serum level of sIL6R are predicted to respond poorly to preoperative chemoradiotherapy, therefore, their exclusion from this treatment may be considered. Persistent systemic inflammation is implicated as a possible mechanism of resistance to this therapy.

Expression and gene amplification of actinin-4 in invasive ductal carcinoma of the pancreas.

PURPOSE: An invasive growth pattern is one of the hallmarks of pancreatic ductal carcinoma. Actinin-4 is an actin-binding protein associated with enhanced cell motility, invasive growth, and lymph node metastasis. Actinin-4 might play an important role in the development and progression of pancreatic cancer. EXPERIMENTAL DESIGN: The expression of actinin-4 was examined immunohistochemically in 173 cases of invasive pancreatic ductal carcinoma. The copy number of the actinin-4 (ACTN4) gene was calculated by fluorescence in situ hybridization. The expression of actinin-4 was stably knocked down by short hairpin RNA, and tumorigenicity was evaluated by orthotopic implantation into mice with severe combined immunodeficiency. RESULTS: The expression level of actinin-4 was increased in 109 (63.0%) of 173 cases of pancreatic cancer. Kaplan-Meier survival curves revealed that patients with increased expression of actinin-4 had a significantly poorer outcome (P=0.00001, log-rank test). Multivariate analysis by the Cox proportional hazard model showed that high expression of actinin-4 was the most significant independent negative predictor of survival (hazard ratio, 2.33; P=0.000009). Amplification (defined as more than four copies per interphase nucleus) of the ACTN4 gene was detected in 11 (37.9%) of 29 cases showing increased expression of actinin-4. Knockdown of actinin-4 expression inhibited the destructive growth of cancer cells in the pancreatic parenchyma. CONCLUSION: Recurrent amplification of chromosome 19q13.1-2 has been reported in pancreatic cancer, but the exact target gene has not been identified. Actinin-4 contributes to the invasive growth of pancreatic ductal carcinoma, and ACTN4 is one of the candidate oncogenes in this chromosome locus.

Serum albumin-associated peptides of patients with uterine endometrial cancer.

The incidence of endometrial cancer is predicted to increase in developed countries. Because of the relatively high incidence of complications and low diagnostic sensitivity associated with endometrial tissue sampling, there is an urgent need for the development of a safe and non-invasive diagnostic method. The proteomic spectrum of albumin-associated peptides was obtained from a total of 125 serum samples (92 from endometrial cancer patients and 33 from controls) by matrix-assisted laser desorption/ionization hybrid quadrupole time-of-flight mass spectrometry, and the candidate markers were selected by the Mann-Whitney U-test and receiver operator characteristics analysis. We selected three mass peaks at 4769, 6254 and 11 792 m/z from a total of 507 peaks as distinguishing cancer patients from controls (P < 0.00001 and area under curve of over 0.8). When the cut-off points were defined as the averages of the values in the controls + 2 SD, the combination of the three peptides detected endometrial cancer with a sensitivity of 65.2% (60/92). Even stage I early endometrial cancers were detected with a sensitivity of 60.3% (38/63). Unfortunately, the three peptides were also detected in 44.6% (33/74) of myoma uteri patients, indicating that they are not specific to endometrial cancer. Although a large-scale study is necessary to confirm the clinical significance of the peptide biomarkers identified in this study, direct profiling of serum-albumin-bound peptides by high-resolution mass spectrometry was proven to have potential as a means of identifying biomarkers for a variety of diseases.

Possible detection of pancreatic cancer by plasma protein profiling.

The survival rate of pancreatic cancer patients is the lowest among those with common solid tumors, and early detection is one of the most feasible means of improving outcomes. We compared plasma proteomes between pancreatic cancer patients and sex- and age-matched healthy controls using surface-enhanced laser desorption/ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. Proteomic spectra were generated from a total of 245 plasma samples obtained from two institutes. A discriminating proteomic pattern was extracted from a training cohort (71 pancreatic cancer patients and 71 healthy controls) using a support vector machine learning algorithm and was applied to two validation cohorts. We recognized a set of four mass peaks at 8,766, 17,272, 28,080, and 14,779 m/z, whose mean intensities differed significantly (Mann-Whitney U test, P < 0.01), as most accurately discriminating cancer patients from healthy controls in the training cohort [sensitivity of 97.2% (69 of 71), specificity of 94.4% (67 of 71), and area under the curve value of 0.978]. This set discriminated cancer patients in the first validation cohort with a sensitivity of 90.9% (30 of 33) and a specificity of 91.1% (41 of 45), and its discriminating capacity was further validated in an independent cohort at a second institution. When combined with CA19-9, 100% (29 of 29 patients) of pancreatic cancers, including early-stage (stages I and II) tumors, were detected. Although a multi-institutional large-scale study will be necessary to confirm clinical significance, the biomarker set identified in this study may be applicable to using plasma samples to diagnose pancreatic cancer.

Possible prediction of chemoradiosensitivity of esophageal cancer by serum protein profiling.

PURPOSE: Establishment of a reliable method of predicting the efficacy of chemotherapy and radiotherapy is necessary to provide the most suitable treatment for each cancer patient. We investigated whether proteomic profiles of serum samples obtained from untreated patients were capable of being used to predict the efficacy of combined preoperative chemoradiotherapy against esophageal cancer. EXPERIMENTAL DESIGN: Proteomic spectra were obtained from a training set of 27 serum samples (15 pathologically diagnosed responders to preoperative chemoradiotherapy and 12 nonresponders) by surface-enhanced laser desorption and ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. A proteomic pattern prediction model was constructed from the training set by machine learning algorithms, and it was then tested with an independent validation set consisting of serum samples from 15 esophageal cancer patients in a blinded manner. RESULTS: We selected a set of four mass peaks, at 7,420, 9,112, 17,123, and 12,867 m/z, from a total of 859 protein peaks, as perfectly distinguishing responders from nonresponders in the training set with a support vector machine algorithm. This set of peaks (i.e., the classifier) correctly diagnosed chemoradiosensitivity in 93.3% (14 of 15) of the cases in the validation set. CONCLUSIONS: Recent mass spectrometric approaches have revealed that serum contains a large volume of information that reflects the microenvironment of diseased organs. Although a multi-institutional large-scale study will be necessary to confirm each component of the classifier, there is a subtle but definite difference in serum proteomic profile between responders and nonresponders to chemoradiotherapy.