Genetic-based biomarkers and next-generation sequencing: the future of personalized care in colorectal cancer

Tumor biomarkers for diagnosis, prognosis and targeted therapy

Tumor biomarkers, the substances which are produced by tumors or the body's responses to tumors during tumorigenesis and progression, have been demonstrated to possess critical and encouraging value in screening and early diagnosis, prognosis prediction, recurrence detection, and therapeutic efficacy monitoring of cancers. Over the past decades, continuous progress has been made in exploring and discovering novel, sensitive, specific, and accurate tumor biomarkers, which has significantly promoted personalized medicine and improved the outcomes of cancer patients, especially advances in molecular biology technologies developed for the detection of tumor biomarkers. Herein, we summarize the discovery and development of tumor biomarkers, including the history of tumor biomarkers, the conventional and innovative technologies used for biomarker discovery and detection, the classification of tumor biomarkers based on tissue origins, and the application of tumor biomarkers in clinical cancer management. In particular, we highlight the recent advancements in biomarker-based anticancer-targeted therapies which are emerging as breakthroughs and promising cancer therapeutic strategies. We also discuss limitations and challenges that need to be addressed and provide insights and perspectives to turn challenges into opportunities in this field. Collectively, the discovery and application of multiple tumor biomarkers emphasized in this review may provide guidance on improved precision medicine, broaden horizons in future research directions, and expedite the clinical classification of cancer patients according to their molecular biomarkers rather than organs of origin.

Target DNA- and pH-responsive DNA hydrogel-based capillary assay for the optical detection of short SARS-CoV-2 cDNA

DNA is recognized as a powerful biomarker for clinical diagnostics because its specific sequences are closely related to the cause and development of diseases. However, achieving rapid, low-cost, and sensitive detection of short-length target DNA still remains a considerable challenge. Herein, we successfully combine the catalytic hairpin assembly (CHA) technique with capillary action to develop a new and cost-effective method, a target DNA- and pH-responsive DNA hydrogel–based capillary assay, for the naked eye detection of 24 nt short single-stranded target DNA. Upon contact of target DNA, three individual hairpin DNAs hybridize with each other to sufficiently amplify Y-shaped DNA nanostructures (Y-DNA) until they are completely consumed via CHA cycling reactions. Each arm of the resultant Y-DNA contains sticky ends with i-motif DNA structure-forming sequences that can be self-assembled in an acidic environment (pH 5.0) to form target DNA- and pH-responsive DNA hydrogels by means of i-motif DNA-driven crosslinking. When inserting a capillary tube in the resultant solution, the liquid level inside clearly reduces due to the decrease in capillary force induced by the gels. In this way, the developed assay demonstrates sensitive and quantitative detection, with a detection limit of approximately 10 pM of 24 nt short complementary DNA (cDNA) targeting SARS-CoV-2 RNA genes at room temperature within 1 h. The assay is further shown to successfully detect target cDNA in serum, and it is also applied to detect several types of target sequences. Requiring no analytic equipment, precise temperature control, or enzymatic reactions, the developed DNA hydrogel–based capillary assay has potential as a promising naked eye detection platform for target DNA in resource-limited clinical settings.

Catalytic hairpin DNA assembly-based chemiluminescent assay for the detection of short SARS-CoV-2 target cDNA

Colorimetric sensors are recognized as a promising means for target molecule detection as they provide rapid, cost-effective, and facile sensing visible to the naked eye. Challenges remain though in terms of their detection sensitivity and specificity for short-length target genes. Herein, we demonstrate the successful combination of the catalytic hairpin DNA assembly (CHA) approach with enzyme-linked immunosorbent assay (ELISA)-mimicking techniques for a simple, sensitive, and sequence-specific colorimetric assay to detect short SARS-CoV-2 target cDNA. In the developed CHA-based chemiluminescent assay, a low concentration of target cDNA is continuously recycled to amplify dimeric DNA probes from two biotinylated hairpin DNA until the hairpin DNA is completely consumed. The dimeric DNA probes are effectively immobilized in a neutravidin-coated microplate well and then capture neutravidin-conjugated horseradish peroxidase via biotin-neutravidin interactions, resulting in a sensitive and selective colorless-to-blue color change. The developed sensing system exhibits a high sensitivity with a detection limit of ~1 nM for target cDNA as well as the ability to precisely distinguish a single-base mismatched mutant gene within 2 h. As the proposed system does not require complex protocols or expensive equipment to amplify target cDNA, it has the potential to be utilized as a powerful tool to improve the detection sensitivity of target genes for clinical diagnostics with colorimetric detection.

A primer on machine learning techniques for genomic applications

High throughput sequencing technologies have enabled the study of complex biological aspects at single nucleotide resolution, opening the big data era. The analysis of large volumes of heterogeneous "omic" data, however, requires novel and efficient computational algorithms based on the paradigm of Artificial Intelligence. In the present review, we introduce and describe the most common machine learning methodologies, and lately deep learning, applied to a variety of genomics tasks, trying to emphasize capabilities, strengths and limitations through a simple and intuitive language. We highlight the power of the machine learning approach in handling big data by means of a real life example, and underline how described methods could be relevant in all cases in which large amounts of multimodal genomic data are available.

The Liquid Biopsy in the Management of Colorectal Cancer: An Overview

Currently, there is a crucial need for novel diagnostic and prognostic biomarkers with high specificity and sensitivity in patients with colorectal cancer. A "liquid biopsy" is characterized by the isolation of cancer-derived components, such as circulating tumor cells, circulating tumor DNA, microRNAs, long non-coding RNAs, and proteins, from peripheral blood or other body fluids and their genomic or proteomic assessment. The liquid biopsy is a minimally invasive and repeatable technique that could play a significant role in screening and diagnosis, and predict relapse and metastasis, as well as monitoring minimal residual disease and chemotherapy resistance in colorectal cancer patients. However, there are still some practical issues that need to be addressed before liquid biopsy can be widely used in clinical practice. Potential challenges may include low amounts of circulating tumor cells and circulating tumor DNA in samples, lack of pre-analytical and analytical consensus, clinical validation, and regulatory endorsement. The aim of this review was to summarize the current knowledge of the role of liquid biopsy in the management of colorectal cancer.

Identification of the Mutational Landscape of Gynecological Malignancies

Background: Cancer is a complex disease that arises from the accumulation of multiple genetic and non-genetic changes. Advances in sequencing technologies have allowed unbiased and global analysis of patient-derived tumor samples and the discovery of genetic and transcriptional changes in key genes and oncogenic pathways. That in turn has facilitated a better understanding of the underlying causes of cancer initiation and progression, resulting in new therapeutic targets. Methods: In our study, we have analyzed the mutational landscape of gynecological malignancies using datasets from The Cancer Genome Atlas (TCGA). We have also analyzed Oncomine datasets to establish the impact of their alteration on disease recurrence and survival of patients. Results: In this study, we analyzed a series of different gynecological malignancies for commonly occurring genetic and non-genetic alterations. These studies show that white women have higher incidence of gynecological malignancies. Furthermore, our study identified 16 genes that are altered at a frequency >10% among all of the gynecological malignancies and tumor suppressor TP53 is the most altered gene in these malignancies (>50% of the cases). The top 16 genes fall into the categories of either tumor suppressor or oncogenes and a subset of these genes are associated with poor prognosis, some affecting recurrence and survival of ovarian cancer patients. Conclusion: In sum, our study identified 16 major genes that are broadly mutated in a large majority of gynecological malignancies and in some cases predict survival and recurrence in patients with gynecological malignancies. We predict that the functional studies will determine their relative role in the initiation and progression of gynecological malignancies and also establish if some of them represents drug targets for anti-cancer therapy.

Biomarkers for detection, prognosis and therapeutic assessment of neurological disorders

Neurological disorders have aroused a significant concern among the health scientists globally, as diseases such as Parkinson's, Alzheimer's and dementia lead to disability and people have to live with them throughout the life. Recent evidence suggests that a number of environmental chemicals such as pesticides (paraquat) and metals (lead and aluminum) are also the cause of these diseases and other neurological disorders. Biomarkers can help in detecting the disorder at the preclinical stage, progression of the disease and key metabolomic alterations permitting identification of potential targets for intervention. A number of biomarkers have been proposed for some neurological disorders based on laboratory and clinical studies. In silico approaches have also been used by some investigators. Yet the ideal biomarker, which can help in early detection and follow-up on treatment and identifying the susceptible populations, is not available. An attempt has therefore been made to review the recent advancements of in silico approaches for discovery of biomarkers and their validation. In silico techniques implemented with multi-omics approaches have potential to provide a fast and accurate approach to identify novel biomarkers.

Activation of the mTOR Pathway by Oxaliplatin in the Treatment of Colorectal Cancer Liver Metastasis

Background

Standard of care treatment for colorectal cancer liver metastasis consists of a cytotoxic chemotherapy in combination with a targeted agent. Clinical trials have guided the use of these combinatory therapies, but it remains unclear what the optimal combinations of cytotoxic chemotherapy with a targeted agent are.

Methods

Using a genomic based approach, gene expression profiling was obtained from tumor samples of patient with colorectal cancer liver metastasis who received an oxaliplatin based therapy. Early passaged colorectal cancer liver metastasis cell lines and patient derived xenografts of colorectal cancer liver metastasis were then treated with oxaliplatin and a mTOR inhibitor.

Results

Gene set enrichment analysis revealed that the mTOR pathway was activated in patients receiving oxaliplatin based therapy. Treatment of early passaged colorectal cancer lines and patient derived xenografts with oxaliplatin resulted in activation of the mTOR pathway. Combination therapy with oxaliplatin and a mTOR inhibitor resulted in a synergistic effect both in vitro and in vivo.

Conclusion

Our findings suggest a genomic based approach can be used to identify optimal combinations of cytotoxic chemotherapy with a targeted agent and that these observations can be validated both in vitro and in vivo using patient derived colorectal cancer cell lines and patient derived xenografts prior to clinical use.

Decision Making on Medical Innovations in a Changing Health Care Environment: Insights from Accountable Care Organizations and Payers on Personalized Medicine and Other Technologies

BACKGROUND

New payment and care organization approaches, such as those of accountable care organizations (ACOs), are reshaping accountability and shifting risk, as well as decision making, from payers to providers, within the Triple Aim context of health reform. The Triple Aim calls for improving experience of care, improving health of populations, and reducing health care costs.

OBJECTIVES

To understand how the transition to the ACO model impacts decision making on adoption and use of innovative technologies in the era of accelerating scientific advancement of personalized medicine and other innovations.

METHODS

We interviewed representatives from 10 private payers and 6 provider institutions involved in implementing the ACO model (i.e., ACOs) to understand changes, challenges, and facilitators of decision making on medical innovations, including personalized medicine. We used the framework approach of qualitative research for study design and thematic analysis.

RESULTS

We found that representatives from the participating payer companies and ACOs perceive similar challenges to ACOs' decision making in terms of achieving a balance between the components of the Triple Aim-improving care experience, improving population health, and reducing costs. The challenges include the prevalence of cost over care quality considerations in ACOs' decisions and ACOs' insufficient analytical and technology assessment capacity to evaluate complex innovations such as personalized medicine. Decision-making facilitators included increased competition across ACOs and patients' interest in personalized medicine.

CONCLUSIONS

As new payment models evolve, payers, ACOs, and other stakeholders should address challenges and leverage opportunities to arm ACOs with robust, consistent, rigorous, and transparent approaches to decision making on medical innovations.

Quantitative Detection and Resolution of BRAF V600 Status in Colorectal Cancer Using Droplet Digital PCR and a Novel Wild-Type Negative Assay

A need exists for robust and cost-effective assays to detect a single or small set of actionable point mutations, or a complete set of clinically informative mutant alleles. Knowledge of these mutations can be used to alert the clinician to a rare mutation that might necessitate more aggressive clinical monitoring or a personalized course of treatment. An example is BRAF, a (proto)oncogene susceptible to either common or rare mutations in codon V600 and adjacent codons. We report a diagnostic technology that leverages the unique capabilities of droplet digital PCR to achieve not only accurate and sensitive detection of BRAF(V600E) but also all known somatic point mutations within the BRAF V600 codon. The simple and inexpensive two-well droplet digital PCR assay uses a chimeric locked nucleic acid/DNA probe against wild-type BRAF and a novel wild-type-negative screening paradigm. The assay shows complete diagnostic accuracy when applied to formalin-fixed, paraffin-embedded tumor specimens from metastatic colorectal cancer patients deficient for Mut L homologue-1.

Germ line polymorphisms as predictive markers for pre-surgical radiochemotherapy in locally advanced rectal cancer: a 5-year literature update and critical review

PURPOSE

Locally advanced rectal cancer is currently treated with pre-surgical radiotherapy and chemotherapy. Approximately one-half of patients obtain a relevant shrinkage/disappearance of tumour, with major clinical advantages. The remaining patients, in contrast, show no benefit and possibly need alternative treatment. To provide the best therapeutic option for each individual patient, predictive markers have been widely researched. This review was undertaken to evaluate recent progress made in this field.

METHODS

A systematic literature search was performed using PubMed and Scopus database, focused on germ line gene polymorphisms as biomarkers and response and toxicity as outcomes. Because an exhaustive previous review was available describing findings up to 2008, we restricted our analysis to the last 5 years.

RESULTS

Ten original research articles were found, reporting promising results for some candidate genes in drug metabolism (TYMS, MTHFR), DNA repair (XRCC1, OGG1, CCND1) and inflammation (SOD2, TGFB1)/immunity (IL13) pathways, but with no firm conclusion. All the studies had small sample size and were defined as exploratory. This review highlights pivotal molecular, clinical, genetic and statistical issues in the investigation of genetic polymorphisms as outcome predictors for rectal cancer and offers suggestions for future development.

CONCLUSIONS

What emerges is a clear need for new proposals, especially in view of the increasing evidence for tumour-host and gene-gene interactions during anticancer treatment, together with stronger adherence to proper methodological requirements.

Challenges of coverage policy development for next-generation tumor sequencing panels: experts and payers weigh in

BACKGROUND

Next-generation tumor sequencing (NGTS) panels, which include multiple established and novel targets across cancers, are emerging in oncology practice, but lack formal positive coverage by US payers. Lack of coverage may impact access and adoption. This study identified challenges of NGTS coverage by private payers.

METHODS

We conducted semi-structured interviews with 14 NGTS experts on potential NGTS benefits, and with 10 major payers, representing more than 125,000,000 enrollees, on NGTS coverage considerations. We used the framework approach of qualitative research for study design and thematic analyses and simple frequencies to further describe findings.

RESULTS

All interviewed payers see potential NGTS benefits, but all noted challenges to formal coverage: 80% state that inherent features of NGTS do not fit the medical necessity definition required for coverage, 70% view NGTS as a bundle of targets versus comprehensive tumor characterization and may evaluate each target individually, and 70% express skepticism regarding new evidence methods proposed for NGTS. Fifty percent of payers expressed sufficient concerns about NGTS adoption and implementation that will preclude their ability to issue positive coverage policies.

CONCLUSIONS

Payers perceive that NGTS holds significant promise but, in its current form, poses disruptive challenges to coverage policy frameworks. Proactive multidisciplinary efforts to define the direction for NGTS development, evidence generation, and incorporation into coverage policy are necessary to realize its promise and provide patient access. This study contributes to current literature, as possibly the first study to directly interview US payers on NGTS coverage and reimbursement.

Body fluid biomarkers in multiple sclerosis: how far we have come and how they could affect the clinic now and in the future

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system, which affects over 2.5 million people worldwide. Although MS has been extensively studied, many challenges still remain in regards to treatment, diagnosis and prognosis. Typically, prognosis and individual responses to treatment are evaluated by clinical tests such as the expanded disability status scale, MRI and presence of oligoclonal bands in the cerebrospinal fluid. However, none of these measures correlates strongly with treatment efficacy or disease progression across heterogeneous patient populations and subtypes of MS. Numerous studies over the past decades have attempted to identify sensitive and specific biomarkers for diagnosis, prognosis and treatment efficacy of MS. The objective of this article is to review and discuss the current literature on body fluid biomarkers in MS, including research on potential biomarker candidates in the areas of miRNA, mRNA, lipids and proteins.

Biomarker testing for breast, lung, and gastroesophageal cancers at NCI designated cancer centers

BACKGROUND

Molecular biomarkers, a cornerstone of precision oncology, are critical in breast, gastroesophageal, and non-small cell lung cancer management (BC, GEC, NSCLC). Testing practices are intensely debated, impacting diagnostic quality and affecting pathologists, oncologists and patients. However, little is known about testing approaches used in practice. Our study described biomarker practices in BC, GEC, and NSCLC at the leading US cancer centers.

METHODS

We conducted a survey of the National Cancer Institute (NCI) designated centers on BC, GEC, and NSCLC biomarker testing. We used simple frequencies to describe practices, two-sided Fisher's exact test and two-sided McNemar's test for cross-cancer comparison. All statistical tests were two-sided.

RESULTS

For BC human epidermal growth factor receptor 2 (HER2), 39% of centers combine guidelines by using in situ hybridization (ISH) and immunohistochemistry (IHC) concurrently, and 21% reflex-test beyond guideline-recommended IHC2+. For GEC HER2, 44% use ISH and IHC concurrently, and 28% reflex-test beyond IHC2+. In NSCLC, the use of IHC is limited to 4% for epidermal growth factor receptor (EGFR) and 7% for anaplastic lymphoma kinase (ALK). 43.5% test NSCLC biomarkers on oncologist order; 34.5% run all biomarkers upfront, and 22% use a sequential protocol. NSCLC external testing is statistically significantly higher than BC (P < .0001) and GEC (P < .0001). NSCLC internally developed tests are statistically significantly more common than BC (P < .0001) and GEC (P < .0001).

CONCLUSIONS

At the NCI cancer centers, biomarker testing practices vary, but exceeding guidelines is a common practice for established biomarkers and emerging practice for newer biomarkers. Use of internally developed tests declines as biomarkers mature. Implementation of multibiomarker protocols is lagging. Our study represents a step toward developing a biomarker testing practice landscape.

A programmable method for massively parallel targeted sequencing

We have developed a targeted resequencing approach referred to as Oligonucleotide-Selective Sequencing. In this study, we report a series of significant improvements and novel applications of this method whereby the surface of a sequencing flow cell is modified in situ to capture specific genomic regions of interest from a sample and then sequenced. These improvements include a fully automated targeted sequencing platform through the use of a standard Illumina cBot fluidics station. Targeting optimization increased the yield of total on-target sequencing data 2-fold compared to the previous iteration, while simultaneously increasing the percentage of reads that could be mapped to the human genome. The described assays cover up to 1421 genes with a total coverage of 5.5 Megabases (Mb). We demonstrate a 10-fold abundance uniformity of greater than 90% in 1 log distance from the median and a targeting rate of up to 95%. We also sequenced continuous genomic loci up to 1.5 Mb while simultaneously genotyping SNPs and genes. Variants with low minor allele fraction were sensitively detected at levels of 5%. Finally, we determined the exact breakpoint sequence of cancer rearrangements. Overall, this approach has high performance for selective sequencing of genome targets, configuration flexibility and variant calling accuracy.

Recent advances in personalized colorectal cancer research

Colorectal cancer is one of the most prevalent cancers and a leading cause ofcancer-related death. It is also curable if detected early. The prognosis for metastatic colorectal cancer remains poor and resistance to chemotherapy is still a major obstacle in effective treatment. While many patients do not clinically benefit from chemotherapy, others experience adverse reactions resulting in dose modifications or treatment withdrawal, thereby reducing treatment efficacy. Researchefforts attempt to identify reliable biomarkers which will guide clinicians in decision making, while matching suitable therapeutic regimens. We here review currently known molecular biomarkers used for the personalized treatment of colorectal cancer.