Critical comments for roles of biomarkers in the diagnosis and treatment of cancer

The Individual and Societal Burden of Treatment-Resistant Depression: An Overview

Major depressive disorder is characterized by depressed mood and/or anhedonia with neurovegetative symptoms and neurocognitive changes affecting an individual's functioning in multiple aspects of life. Treatment outcomes with commonly used antidepressants remain suboptimal. Treatment-resistant depression (TRD) should be considered after inadequate improvement with two or more antidepressant treatments of adequate dose and duration. TRD has been associated with increased disease burden including higher associated costs (both socially and financially) affecting both the individual and society. Additional research is needed to better understand the long-term burden of TRD to both the individual and society.

Gastric juice non-coding RNAs as potential biomarkers for gastric cancer

Gastric cancer (GC), being one of the most common malignant human tumors, occupies the second position in the structure of mortality in men and women. High rates of morbidity and mortality in this pathology determine its extremely high clinical and social significance. Diagnosis and timely treatment of precancerous pathology is the main way to reduce morbidity and mortality, and early detection of GC and its adequate treatment improve prognosis. The ability to accurately predict the development of GC and start treatment on time, as well as the ability to determine the stage of the disease if the diagnosis is confirmed - non-invasive biomarkers can become the key to solving these and many other problems of modern medicine. One of the promising biomarkers being studied are non-coding RNAs, namely, miсroRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). They are involved in a wide range of processes, including apoptosis, proliferation, differentiation, angiogenesis, which play a critical role in the development of GC oncogenesis. In addition, they are quite specific and stable due to their carriers (extracellular vesicles or Argonaute 2 protein) and can be detected in various human biological fluids, in particular gastric juice. Thus, miRNAs, lncRNAs, and circRNAs isolated from the gastric juice of GC patients are promising preventive, diagnostic and prognostic non-invasive biomarkers. This review article presents the characteristics of circulating or extracellular miRNAs, lncRNAs, and circRNAs in gastric juice, allowing their use in the GC preventive, diagnosis, prognosis and monitoring therapy.

Construction and Validation of a Protein-associated Prognostic Model for Gastrointestinal Cancer

Background Gastrointestinal cancer (GIC) is a prevalent and lethal malignant tumor. It is obligatory to investigate innovative biomarkers for the diagnosis and prognosis. Proteins play a crucial role in regulating the occurrence and progression of GIC. However, the prognostic value of proteins is unclear in GIC.

OBJECTIVE

This paper aims to identify the hub prognosis-related proteins (PAPs) and construct a prognosis model for GIC patients for clinical application.

METHODS

Protein expression data of GIC was obtained from The Cancer Proteome Atlas (TCPA) and downloaded the clinicopathological data from The Cancer Genome Atlas database (TCGA). Besides, hub proteins were filtrated via univariate and multivariate Cox regression analysis. Moreover, survival analysis and nomogram were used to predict overall survival (OS). We used the calibration curves to assess the consistency of predictive and actual survival rates. The consistency index (C-index) was used to evaluate the prognostic ability of the predictive model. Furthermore, functional enrichment analysis and protein co-expression of PAPs were used to explore their roles in GIC.

RESULTS

Finally, a prognosis model was conducted based on ten PAPs (CYCLIND1, DVL3, NCADHERIN, SYK, ANNEXIN VII, CD20, CMET, RB, TFRC, and PREX1). The risk score calculated by the model was an independent prognostic predictor. Compared with the high-risk subgroup, the low-risk subgroup had better OS. In the TCGA cohort, the area under the curve value of the receiver operating characteristic curve of the prognostic model was 0.692. The expression of proteins and risk score had a significant association with the clinicopathological characteristics of GIC. Besides, a nomogram based on GIC clinicopathological features and risk scores could properly predict the OS of individual GIC patients. The C-index is 0.71 in the TCGA cohort and 0.73 in the GEO cohort.

CONCLUSION

The results indicate that the risk score is an independent prognostic biomarker and is related to the malignant clinical features of GIC patients. Besides, several PAPs associated with the survival and clinicopathological characteristics of GIC might be potential biomarkers for GIC diagnosis and treatment.

Predictive biomarkers of colorectal cancer

Colorectal cancer is one of the top leading causes of cancer mortality worldwide, especially in China. However, most of the current treatments are invasive and can only be applied to very few cancers. The earlier a malignant tumor is diagnosed, the higher the patient's survival rate. In this study, we proposed a computational framework to identify highly-reliable and easierly-detectable biomarkers capable of secreting into blood, urine and saliva by integrating transcriptomics and proteomics data at the system biology level. First, a large number of transcriptome data were processed to identify candidate biomarkers for colorectal cancer. Second, three classified models are constructed to predict biomarkers for colorectal cancer capable of secreting into blood, urine and saliva, which are effective disease diagnosis media to facilitate clinical screening. Then biological functions and molecular mechanisms of the candidate biomarkers of colorectal cancer are inferred utilizing multi-source biological knowledge and literature mining. Furthermore, the classification power of different combinations of candidate biomarkers is verified by machine learning models. In addition, the targeted drugs of the predicted biomarkers are further analyzed to provide assistance for clinical treatment of colorectal cancer. In this paper, our proposed computational model not only provides the effective candidate biomarkers ESM1, CTHRC1, AZGP1 for colorectal cancer capable of secreting into blood, urine and saliva, but also helps to understand the molecular mechanism of colorectal cancer. This computational framework can span the huge gap between transcriptome and proteomics, which can easily be applied to the biomarker research for other types of tumor.

Accreditation, setting and experience as indicators to assure quality in oncology biomarker testing laboratories

BACKGROUND

Predictive biomarkers allow clinicians to optimise cancer treatment decisions. Therefore, molecular biomarker test results need to be accurate and swiftly available. To ensure quality of oncology biomarker testing, external quality assessments (EQA) for somatic variant analyses were organised. This study hypothesised whether laboratory characteristics influence the performance of laboratories and whether these can be imposed before authorisation of biomarker testing.

METHODS

Longitudinal EQA data from the European Society of Pathology were available over six (metastatic colorectal cancer) and four years (non-small cell lung cancer), including the percentage of analysis errors and technical failures, and information on laboratory characteristics (accreditation status, laboratory setting, number of samples analysed and detection method). Statistical models for repeated measurements were used to analyse the association between the EQA results and the laboratory characteristics.

RESULTS

Laboratory accreditation was associated with fewer analysis errors in early stages of biomarker introduction into the laboratory. Analysing more samples, or university and research laboratories showed better performance. Changing the detection method did not have an effect.

CONCLUSION

The indicators support the clinicians in choosing molecular pathology laboratories by improving quality assurance and guaranteeing patient safety. Accreditation of laboratories, centralisation of biomarker testing or a university and research setting should be stimulated.

A stitch in time saves nine: external quality assessment rounds demonstrate improved quality of biomarker analysis in lung cancer

Biomarker analysis has become routine practice in the treatment of non-small cell lung cancer (NSCLC). To ensure high quality testing, participation to external quality assessment (EQA) schemes is essential. This article provides a longitudinal overview of the EQA performance for EGFR, ALK, and ROS1 analyses in NSCLC between 2012 and 2015.

The four scheme years were organized by the European Society of Pathology according to the ISO 17043 standard. Participants were asked to analyze the provided tissue using their routine procedures.

Analysis scores improved for individual laboratories upon participation to more EQA schemes, except for ROS1 immunohistochemistry (IHC). For EGFR analysis, scheme error rates were 18.8%, 14.1% and 7.5% in 2013, 2014 and 2015 respectively. For ALK testing, error rates decreased between 2012 and 2015 by 5.2%, 3.2% and 11.8% for the fluorescence in situ hybridization (FISH), FISH digital, and IHC subschemes, respectively. In contrast, for ROS1 error rates increased between 2014 and 2015 for FISH and IHC by 3.2% and 9.3%. Technical failures decreased over the years for all three markers.

Results show that EQA contributes to an ameliorated performance for most predictive biomarkers in NSCLC. Room for improvement is still present, especially for ROS1 analysis.

CA-125: an inaccurate surveillance tool immediately after cytoreductive surgery and hyperthermic intraoperative chemotherapy (CRS-HIPEC)?

OBJECTIVE

This study seeks to evaluate pre and post-operative CA-125 in patients undergoing complete cytoreduction surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC), and understand the time frame before values normalise allowing use as a surveillance tool to resume.

METHODS

A retrospective review was carried out of 94 patients undergoing CRS-HIPEC to compare pre-operative CA-125 values, measured within one week prior to surgery to post-operative readings within the first 30 d. Raised CA-125 was defined using as a value >35 U/ml.

RESULTS

Of 63 (67%) patients with normal pre-operative CA-125, 22 (35%) had raised post-operative CA-125, and consisted of patients with colorectal (n = 8), appendiceal (n = 6), ovarian (n = 4) or other (n = 4) cancers. The average peak CA-125 was 80 U/ml occurring on median 10th post-operative day (POD) (range 7-30). The median day of normalisation for patients with normal pre-operative and raised post-operative CA-125 was 57 (range 28-115). The median day of normalisation for patients with raised pre-operative CA-125 was POD 41 (range 1-114). Notably 10 patients had initial normalisation (median POD 1, range 1-6), followed by subsequent raised value (median POD 10, range 5-40) and re-normalisation (median POD 47, range 19-104).

DISCUSSION

For patients with raised pre-operative CA-125 an immediate post-operative CA-125 within 3 d may be useful to assess normalisation following surgery. Aside from immediate measurement CA-125 is misleading and should not be measured post-operatively within the first 3 months after surgery following which its use as a surveillance marker can resume.

Approaches to uncovering cancer diagnostic and prognostic molecular signatures

The recent rapid development of high-throughput technology enables the study of molecular signatures for cancer diagnosis and prognosis at multiple levels, from genomic and epigenomic to transcriptomic. These unbiased large-scale scans provide important insights into the detection of cancer-related signatures. In addition to single-layer signatures, such as gene expression and somatic mutations, integrating data from multiple heterogeneous platforms using a systematic approach has been proven to be particularly effective for the identification of classification markers. This approach not only helps to uncover essential driver genes and pathways in the cancer network that are responsible for the mechanisms of cancer development, but will also lead us closer to the ultimate goal of personalized cancer therapy.

Current status of predictive biomarkers for neoadjuvant therapy in esophageal cancer

Neoadjuvant therapy has been proven to be extremely valuable and is widely used for advanced esophageal cancer. However, a significant proportion of treated patients (60%-70%) does not respond well to neoadjuvant treatments and develop severe adverse effects. Therefore, predictive markers for individualization of multimodality treatments are urgently needed in esophageal cancer. Recently, molecular biomarkers that predict the response to neoadjuvant therapy have been explored in multimodal approaches in esophageal cancer and successful examples of biomarker identification have been reported. In this review, promising candidates for predictive molecular biomarkers developed by using multiple molecular approaches are reviewed. Moreover, treatment strategies based on the status of predicted biomarkers are discussed, while considering the international differences in the clinical background. However, in the absence of adequate treatment options related to the results of the biomarker test, the usefulness of these diagnostic tools is limited and new effective therapies for biomarker-identified nonresponders to cancer treatment should be concurrent with the progress of predictive technologies. Further improvement in the prognosis of esophageal cancer patients can be achieved through the introduction of novel therapeutic approaches in clinical practice.

Neuroimaging and psychiatry: the long road from bench to bedside

Advances in neuroscience have revolutionized our understanding of the central nervous system. Neuroimaging technologies, in particular, have begun to reveal the complex anatomical, physiological, biochemical, genetic, and molecular organizational structure of the organ at the center of that system: the human brain. More recently, neuroimaging technologies have enabled the investigation of normal brain function and are being used to gain important new insights into the mechanisms behind many neuropsychiatric disorders. This research has implications for psychiatric diagnosis, treatment, and risk assessment. However, with some exceptions, neuroimaging is still a research tool, not ready for use in clinical psychiatry.

Toward a neuroimaging treatment selection biomarker for major depressive disorder

IMPORTANCE

Currently, fewer than 40% of patients treated for major depressive disorder achieve remission with initial treatment. Identification of a biological marker that might improve these odds could have significant health and economic impact.

OBJECTIVE

To identify a candidate neuroimaging "treatment-specific biomarker" that predicts differential outcome to either medication or psychotherapy.

DESIGN

Brain glucose metabolism was measured with positron emission tomography prior to treatment randomization to either escitalopram oxalate or cognitive behavior therapy for 12 weeks. Patients who did not remit on completion of their phase 1 treatment were offered enrollment in phase 2 comprising an additional 12 weeks of treatment with combination escitalopram and cognitive behavior therapy.

SETTING

Mood and anxiety disorders research program at an academic medical center.

PARTICIPANTS

Men and women aged 18 to 60 years with currently untreated major depressive disorder.

INTERVENTION

Randomized assignment to 12 weeks of treatment with either escitalopram oxalate (10-20 mg/d) or 16 sessions of manual-based cognitive behavior therapy.

MAIN OUTCOME AND MEASURE

Remission, defined as a 17-item Hamilton depression rating scale score of 7 or less at both weeks 10 and 12, as assessed by raters blinded to treatment.

RESULTS

Positive and negative predictors of remission were identified with a 2-way analysis of variance treatment (escitalopram or cognitive behavior therapy) × outcome (remission or nonresponse) interaction. Of 65 protocol completers, 38 patients with clear outcomes and usable positron emission tomography scans were included in the primary analysis: 12 remitters to cognitive behavior therapy, 11 remitters to escitalopram, 9 nonresponders to cognitive behavior therapy, and 6 nonresponders to escitalopram. Six limbic and cortical regions were identified, with the right anterior insula showing the most robust discriminant properties across groups (effect size = 1.43). Insula hypometabolism (relative to whole-brain mean) was associated with remission to cognitive behavior therapy and poor response to escitalopram, while insula hypermetabolism was associated with remission to escitalopram and poor response to cognitive behavior therapy.

CONCLUSIONS AND RELEVANCE

If verified with prospective testing, the insula metabolism-based treatment-specific biomarker defined in this study provides the first objective marker, to our knowledge, to guide initial treatment selection for depression.

TRIAL REGISTRATION

Registered at clinicaltrials.gov (NCT00367341).

Alternatives for the intensive follow-up after curative resection of colorectal cancer. Potential novel biomarkers for the recommendations

Early diagnosis of recurrence and metastasis of colorectal cancer following surgery of curative intent is of vital importance in terms of survival and quality of life. The consistent implementation of appropriate patient follow-up strategy is therefore essential. Debates over the methodology, evaluation and strategy of follow-up have been known for many years, and continue today. By introducing several follow-up models, the present paper offers different options featuring certain individual, national and international, conceptual and financial aspects. Colorectal cancer is an important public health concern due to its destructive nature and frequency, it is therefore essential to develop new monitoring strategies, involving new biomarkers and extensive clinical validation. Since the recurrence rate is very high in high-risk patients, the improvement of individual patient risk estimates and the utilization of a corresponding follow-up model require broad international co-operation and common practice, along with the determination of optimal levels of evidence.

Detecting circulating tumor cells: current challenges and new trends

Circulating tumor cells (CTCs) in the blood stream play a critical role in establishing metastases. The clinical value of CTCs as a biomarker for early cancer detection, diagnosis, prognosis, prediction, stratification, and pharmacodynamics have been widely explored in recent years. However, the clinical utility of current CTC tests is limited mainly due to methodological constraints. In this review, the pros and cons of the reported CTC assays are comprehensively discussed. In addition, the potential of tumor cell-derived materials as new targets for CTC detection, including circulating tumor microemboli, cell fragments, and circulating DNA, is evaluated. Finally, emerging approaches for CTC detection, including telomerase-based or aptamer-based assays and cell functional analysis, are also assessed. Expectantly, a thorough review of the current knowledge and technology of CTC detection will assist the scientific community in the development of more efficient CTC assay systems.

Polymorphisms in oxidative stress-related genes and mortality in breast cancer patients--potential differential effects by radiotherapy?

We assessed whether variants in 22 oxidative stress-related genes are associated with mortality of breast cancer patients and whether the associations differ according to radiotherapy. Using a prospective cohort of 1348 postmenopausal breast cancer patients, we estimated hazard ratios (HR) and 95% confidence intervals (CI) for 109 single nucleotide polymorphisms (SNPs) using Cox proportional hazards regression. Validation of results was attempted using two Scandinavian studies. Eleven SNPs in MT2A, NFE2L2, NQO1, PRDX1, and PRDX6 were significantly associated with overall mortality after a median follow-up of 5.7 years. Three SNPs in NQO1 (rs2917667) and in PRDX6 (rs7314, rs4916362) were consistently associated with increased risk of dying across all three study populations (pooled: HRNQO1_rs2917667 1.20, 95% CI 1.00-1.44, p = 0.051; HRPRDX6_rs7314 1.16, 95% CI 1.00-1.35, p = 0.056, HRPRDX6_rs4916362 1.14 95% CI 1.00-1.32, p = 0.062). Potential effect modification by radiotherapy was found for CAT_rs769218. In conclusion, genetic variants in NQO1 and PRDX6 may modify breast cancer prognosis.

Present status and problems on molecular targeted therapy of cancer

Numerous clinical trials of molecular targeted drugs for cancer have been conducted, with remarkable results for certain drugs and accumulation of "negative data" causing a hitch in the development plan for some other compounds. Five recent issues and problems of molecular targeted therapies were discussed critically. Drug discovery and effects against driver mutations (activating mutations) and problems: possibility for circumventing inherent and acquired resistance with the aim of achieving radical cure. Synthetic lethality: reasonable patient selection in individualized treatment strategy. Response rate and progression-free survival improvement with or without overall survival benefit and enhancement of toxicity in bevacizumab therapy: best endpoints for the evaluation of effect of antiangiogenic therapy. Negative data on small-molecule targeted therapy, primarily vascular endothelial growth factor tyrosine kinase inhibitors: loose GO or NO-GO decision criteria for further development of new compounds in early clinical trials. Effect of immunotherapy: difficulty to verify by proof of principle study. We are faced to many questions for the development of efficient personalized therapy. Accumulation of scientific global preclinical and clinical evidences is essential to use these new therapeutic modalities for the improvement of oncologic health care.