Early diagnosis based on screening is recognized as one of the most efficient ways of mitigating cancer-associated morbidity and mortality. Therefore, reliable but cost-effective methodologies are needed. By using a portable Raman spectrometer, a small and easily transportable instrument, the needs of modern diagnosis in terms of rapidity, ease of use and flexibility are met. In this study, we analyzed the diagnostic accuracy yielded by the surface-enhanced Raman scattering (SERS)-based profiling of serum, performed with a portable Raman device operating in a real-life hospital environment, in the case of 53 patients with gastrointestinal tumors and 25 control subjects. The SERS spectra of serum displayed intense bands attributed to carotenoids and purine metabolites such as uric acid, xanthine and hypoxanthine, with different intensities between the cancer and control groups. Based on principal component analysis-quadratic discriminant analysis (PCA-QDA), the cancer and control groups were classified with an accuracy of 76.92%. By combining SERS spectra with general inflammatory markers such as C-reactive protein levels, neutrophil counts, platelet counts and hemoglobin levels, the discrimination accuracy was increased to 83.33%. This study highlights the potential of SERS-based liquid biopsy for the point-of-care diagnosis of gastrointestinal tumors using a portable Raman device operating in a clinical setting.

Prostate cancer represents the most encountered urinary malignancy in males over 50 years old, and the second most diagnosed after lung cancer globally. Digital rectal examination and prostatic specific antigen were the long-time standard tools for diagnosis but with a significant risk of overdiagnosis and overtreatment. Magnetic resonance imaging recently entered the diagnosis process, but to this date, there is no specific biomarker that accurately indicates whether to proceed with the prostate biopsy. Research in this area has gone towards this direction, and recently, serum, urine, imagistic, tissue biomarkers, and Risk Calculators promise to help better diagnose and stratify prostate cancer. In order to eliminate the comorbidities that appear along with the diagnosis and treatment of this disease, there is a constant need to implement new diagnostic strategies. Important uro-oncology associations recommend the use of novel biomarkers in the grey area of prostate cancer, to better distinguish the next step in the diagnostic process. Although it is not that simple, they should be integrated according to the clinical policies, and it should be considered that statistical significance does not always equal clinical significance. In this review, we analyzed the contribution of prostate-specific antigen (PSA)-based biomarkers (PHI, PHID, 4Kscore, STHLM3), imagistic techniques (mp-MRI and mp-US), and combined tests in the early diagnosis process of localized prostate cancer.

Prostate cancer is one of the most encountered cancer diseases in men worldwide and in consequence it requires the improvement of therapeutic strategies. For the clinical diagnosis, the standard approach is represented by solid biopsy. From a surgical point of view, this technique represents an invasive procedure that may imply several postoperative complications. To overcome these impediments, many trends are focusing on developing liquid biopsy assays and on implementing them in clinical practice. Liquid samples (blood, urine) are rich in analytes, especially in transcriptomic information provided by genetic markers. Additionally, molecular characterization regarding microRNAs content reveals outstanding prospects in understanding cancer progression mechanisms. Moreover, these analytes have great potential for prostate cancer early detection, more accurate prostate cancer staging and also for decision making respecting therapy schemes. However, there are still questionable topics and more research is needed to standardize liquid biopsy-based techniques.

It is possible to obtain diagnostically relevant data on the changes in biochemical elements brought on by cancer via the use of multivariate analysis of vibrational spectra recorded on biological fluids. Prostate cancer and control groups included in this research generated almost similar SERS spectra, which means that the values of peak intensities present in SERS spectra can only give unspecific and limited information for distinguishing between the two groups. Our diagnostic algorithm for prostate cancer (PCa) differentiation was built using principal component analysis and linear discriminant analysis (PCA-LDA) analysis of spectral data, which has been widely used in spectral data management in many studies and has shown promising results so far. In order to fully utilize the entire SERS spectrum and automatically determine the most meaningful spectral features that can be used to differentiate PCa from healthy patients, we perform a multivariate analysis on both the entire and specific spectral intervals. Using the PCA-LDA model, the prostate cancer and control groups are clearly distinguished in our investigation. The separability of the following two data sets is also evaluated using two alternative discrimination techniques: principal least squares discriminant analysis (PLS-DA) and principal component analysis—support vector machine (PCA-SVM).

Background and objectives: Systematic prostate biopsy (SB) has a low Gleason group (GG) accuracy when compared to final pathology. This may negatively impact the inclusion of patients into specific risk groups and treatment choice. The aim of our study was to assess the GG accuracy of magnetic resonance imaging-ultrasound (MRI-US) fusion prostate biopsy. Materials and Methods: Of a cohort of minimally invasive radical prostatectomy (RP), we selected all patients who were diagnosed with prostate cancer (PCa) via MRI-US fusion biopsy (n = 115). Results: Combined biopsy had the highest rate for GG concordance (61.7% vs. 60.4% for SB vs. 45.3% for MRI-US fusion biopsy) and the lowest for upgrading (20.9% vs. 24.5% for SB vs. 34.9% for MRI-US fusion biopsy), p < 0.0001. No clinical data were predictive for upgrading or downgrading at final pathology. Locally advanced PCa was associated with a high Prostate Imaging-Reporting and Data System (PIRADS) score (p = 0.0014) and higher percentages of positive biopsy cores (PBC)/targeted (p = 0.0002) and PBC/total (p = 0.01). Positive surgical margins were correlated with higher percentages of PBC/systematic (p = 0.003) and PBC/total (p = 0.009). Conclusions: Pre-biopsy prostate MRI improves GG concordance between biopsy and RP. Combined biopsy provides the highest grading accuracy when compared to final pathology. Targeted and systematic biopsy data are predictive for adverse pathologic outcomes.

Primary mesenchymal chondrosarcoma of the kidney is an extremely rare malignant tumor. To our best knowledge, only 9 such cases have been reported so far. In the current paper, we present the case of a 67 year-old patient with recurrent left lumbar pain, increased fatigability and intermittent macroscopic hematuria. He underwent a surgical resection of the left kidney and left hemicolon. The pathological diagnosis was primary extraskeletal renal mesenchymal chondrosarcoma. Overall survival was 9 months, with pulmonary metastasis and local recurrence at 6 months. The management of the patient is described, from the initial differential diagnosis, after the first clinical examination to the surgical resection, with a special emphasis on the surgical procedures that were carried out. Extraskeletal chondrosarcoma of primary origin in the kidney are extremely rare tumors with a highly malignant potential and very poor prognosis. Because the role of chemotherapy or radiation therapy has not been evaluated properly yet, we underline the importance of surgery in the management of such cases as the main and best approach to achieve clinical remission and long-term survival, provided the patient is referred to a surgical consult in time.