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Biomarkers in Medicine is a comprehensive guide to understanding the current and future status of biomarkers. The book features 27 chapters focusing on disease biomarkers for diseases such as cancer, neurodegenerative diseases, cardiac diseases, metabolic conditions and much more. This book supplies readers with the unique insight of experts in multiple specialties in medicine and life sciences who have extensive experience in diagnostics and clinical laboratories. The book includes case studies and practical examples from different classes of biomarkers on different platforms, including new data for biomarkers in different therapeutic indications. In addition to presenting biomarker information, each chapter covers the relevant pathology and also emphasizes on preclinical and clinical manifestation of the disease process. Clinicians managing patients or clinical trials, clinical researchers, clinical laboratories, diagnostic companies, regulatory agencies, medical school graduate students, academic students, and the general public involved in healthcare delivery will all benefit from information presented in this book.

Many cancer patients are diagnosed at a stage in which the cancer is too far advanced to be cured, and most cancer treatments are effective in only a minority of patients undergoing therapy. Thus, there is tremendous opportunity to improve the outcome for people with cancer by enhancing detection and treatment approaches. Biomarkers will be instrumental in making that transition. Advances in biotechnology and genomics have given scientists new hope that biomarkers can be used to improve cancer screening and detection, to improve the drug development process, and to enhance the effectiveness and safety of cancer care by allowing physicians to tailor treatment for individual patients-an approach known as personalized medicine. However, progress overall has been slow, despite considerable effort and investment, and there are still many challenges and obstacles to overcome before this paradigm shift in oncology can become a reality.

Lung cancer is one of the most common cancers in both men and women worldwide. Early diagnosis of lung cancer can significantly increase the chances of a patient's survival, yet early detection has historically been difficult. As a result, there has been a great deal of progress in the development of accurate and fast diagnostic tools in recent years. Lung Cancer and Imaging provides an introduction to both the methods currently used in lung cancer diagnosis and the promising new techniques that are emerging. Areas covered include the major trends and challenges in lung cancer detection and diagnosis, classification of cancer types, lung feature extraction in joint PET/CT images, and algorithms in the area of low dosage CT lung cancer images. Part of Series in Physics and Engineering in Medicine and Biology.

Prepared by world leaders on this topic, Biomarkers in Cancer Screening and Early Detection offers a comprehensive, state-of-the-art perspective on the various research and clinical aspects of cancer biomarkers, from their discovery and development to their validation, clinical utility, and use in developing personalized cancer treatment. * Offers a comprehensive, state-of-the-art perspective on the various research and clinical aspects of cancer biomarkers * Provides immediately actionable information – and hopefully also inspiration – to move discovery and clinical application forward * Offers vital knowledge to help develop personalized cancer treatment for individual patients with specific cancers

Genomics is majorly impacting therapeutics development in medicine. This book contains up-to-date information on the use of genomics in the design and analysis of therapeutic clinical trials with a focus on novel approaches that provide a reliable basis for identifying which patients are most likely to benefit from each treatment. It is oriented to both clinical investigators and statisticians. For clinical investigators, it includes background information on clinical trial design and statistical analysis. For statisticians and others who want to go deeper, it covers state-of-the-art adaptive designs and the development and validation of probabilistic classifiers. The author describes the development and validation of prognostic and predictive biomarkers and their integration into clinical trials that establish their clinical utility for informing treatment decisions for future patients.

Background Pancreatic cancer is associated with an extremely poor prognosis, so new biomarkers that can detect the initial stages are urgently needed. The significance of serum microRNA (miR) levels in pancreatic neoplasm such as pancreatic cancer and intraductal papillary mucinous neoplasm (IPMN) diagnosis remains unclear. We herein evaluated the usefulness of miRs enclosed in serum exosomes (ExmiRs) as diagnostic markers. Methods The ExmiRs from patients with pancreatic cancer ( n  = 32) or IPMN ( n  = 29), and patients without neoplasms (controls; n  = 22) were enriched using ExoQuick-TC™. The expression of ExmiRs was evaluated using a next-generation sequencing analysis, and the selected three miRs through this analysis were confirmed by a quantitative real-time polymerase chain reaction. Results The expression of ExmiR-191, ExmiR-21 and ExmiR-451a was significantly up-regulated in patients with pancreatic cancer and IPMN compared to the controls ( p  < 0.05). A receiver operating characteristic curve analysis showed that the area under the curve and the diagnostic accuracy of ExmiRs were 5–20% superior to those of three serum bulky circulating miRs (e.g.; ExmiR-21: AUC 0.826, accuracy 80.8%. Circulating miR-21: AUC 0.653, accuracy 62.3%). In addition, high ExmiR-451a was associated with mural nodules in IPMN ( p  = 0.010), and high ExmiR-21 was identified as a candidate prognostic factor for the overall survival ( p  = 0.011, HR 4.071, median OS of high-ExmiR-21: 344 days, median OS of low-ExmiR-21: 846 days) and chemo-resistant markers ( p  = 0.022). Conclusions The level of three ExmiRs can thus serve as early diagnostic and progression markers of pancreatic cancer and IPMN, and considered more useful markers than the circulating miRs (limited to these three miRs).

Background Current prognostic prediction models of colorectal cancer (CRC) include only the preoperative measurement of tumor markers, with their available repeated postoperative measurements underutilized. CRC prognostic prediction models were constructed in this study to clarify whether and to what extent the inclusion of perioperative longitudinal measurements of CEA, CA19-9, and CA125 can improve the model performance, and perform a dynamic prediction. Methods The training and validating cohort included 1453 and 444 CRC patients who underwent curative resection, with preoperative measurement and two or more measurements within 12 months after surgery, respectively. Prediction models to predict CRC overall survival were constructed with demographic and clinicopathological variables, by incorporating preoperative CEA, CA19-9, and CA125, as well as their perioperative longitudinal measurements. Results In internal validation, the model with preoperative CEA, CA19-9, and CA125 outperformed the model including CEA only, with the better area under the receiver operating characteristic curves (AUCs: 0.774 vs 0.716), brier scores (BSs: 0.057 vs 0.058), and net reclassification improvement (NRI = 33.5%, 95% CI: 12.3 ~ 54.8%) at 36 months after surgery. Furthermore, the prediction models, by incorporating longitudinal measurements of CEA, CA19-9, and CA125 within 12 months after surgery, had improved prediction accuracy, with higher AUC (0.849) and lower BS (0.049). Compared with preoperative models, the model incorporating longitudinal measurements of the three markers had significant NRI (40.8%, 95% CI: 19.6 to 62.1%) at 36 months after surgery. External validation showed similar results to internal validation. The proposed longitudinal prediction model can provide a personalized dynamic prediction for a new patient, with estimated survival probability updated when a new measurement is collected during 12 months after surgery. Conclusions Prediction models including longitudinal measurements of CEA, CA19-9, and CA125 have improved accuracy in predicting the prognosis of CRC patients. We recommend repeated measurements of CEA, CA19-9, and CA125 in the surveillance of CRC prognosis.

Background Our aim of was to compare importance of the tumor markers (TMs) serum carcinoembryonic antigen (CEA) and carbohydrate antigen (CA) 19-9 in prediction of recurrence after curative gastrectomy for gastric cancer. Methods We reviewed retrospectively the clinical records of 149 patients who underwent curative gastrectomy for stage I–III gastric cancer and whose CEA and CA19-9 levels were determined once preoperatively and for more than 3 years postoperatively. We investigated whether the clinicopathological characteristics of patients including age, sex, pathological disease stage, operative approach, type of gastrectomy, and degree of lymph node dissection as well as preoperative positivity of CEA and CA19-9 were risk factors for recurrence in univariate and multivariate analyses. Rate of recurrence was compared between patients positive and negative for postoperative CEA or CA19-9. We also calculated sensitivity, specificity, positive and negative predictable values of postoperative positivity of CEA and CA19-9 for recurrence. The lead time was compared between CEA and CA19-9 that was defined as the time of the first detection of increases in tumor markers and confirmation of recurrence on imaging modalities. Results The number of patients positive for preoperative CEA was 25 (17%) and for CA19-9 was 11 (7%). Recurrence was confirmed in 29 (19%) patients. Stage III disease, preoperative positivity for CA19-9 but not CEA, and total gastrectomy were risk factors for recurrence in univariate analysis, but stage III disease was the only risk factor for recurrence in multivariate analysis. Forty and 15 patients were positive for postoperative CEA and CA19-9, respectively. The recurrence rate of 47% (7/15) in patients positive for postoperative CA19-9 was greater than that in negative patients (22/134 = 16%), but it did not differ between patients who were positive or negative for postoperative CEA. Specificity for CA19-9 was greater than that for CEA (P < 0.05). The lead time of CEA (3.9 ± 4.7 months) was not different from that of CA19-9 (6.1 ± 7.1 months). Conclusions These results indicate that CA19-9 rather than CEA is likely to be more useful for the detection of recurrence after curative gastrectomy for gastric cancer.

Background This systematic review aimed to gather evidence from research on the current state of liquid biopsy in medical practice, specifically focusing on mutation detection and monitoring. Methods A systematic search was performed via Medline. Results The results of this investigation indicate that liquid biopsy plays a critical role in the detection and management of tumors. This technique gives healthcare providers the ability to gather critical and reliable information that may potentially shape the diagnosis, treatment, and prognosis of a variety of cancers in the near future. This study further reveals that liquid biopsy has several potential shortcomings that may limit its application and use in the healthcare setting. Nevertheless, liquid biopsy remains a valuable tool that is gradually becoming a part of routine healthcare practice in oncology departments and hospitals worldwide. Conclusions The evidence described herein reveals the potential relevance of liquid biopsy as an important prognostic, diagnostic, and theranostic tool. This non-invasive procedure enables healthcare practitioners to detect and monitor genomic alterations and will likely replace tumor tissue biopsy as the standard method for detecting and monitoring mutations in the future. The information obtained herein can enable physicians to make informed decisions regarding current treatment options; however, liquid biopsy has not yet been incorporated into routine clinical diagnostics for cancer patients.