Changing paradigm of cancer therapy: precision medicine by next-generation sequencing

Effects of EGFR driver mutations on pathologic regression in resectable locally advanced non-small cell lung cancer treated with neoadjuvant chemoradiation and completion surgery

OBJECTIVE

We hypothesized that driver mutations in epidermal growth factor receptor (EGFR) are associated with decreased pathologic response to neoadjuvant chemoradiation (NA-ChRT) in locally advanced non-small cell lung cancer (LA-NSCLC).

METHODS

Patients with Stage IIB-IIIA NSCLC treated with NA-ChRT, completion surgery, and underwent molecular profile testing were identified in a lung cancer database. Pathologic response was quantified using: (i) major pathologic response (MPR), (ii) complete pathologic response (pCR), and (iii) mean residual viable tumor cells (MRTC). Two groups were formed based on the presence or absence of driver mutations. Clinical and pathological correlations between the groups were studied.

RESULTS

Forty-seven patients underwent tumor molecular profile testing, NA-ChRT, and completion surgery. Compared to the no-driver mutation group, the driver mutation group had lower MPR (23% vs 71%, p = 0.003), pCR (0% vs 26%, p = 0.02), and higher MRTC (43.4% vs 15.8%, p = 0.009). Univariate analysis showed an increased MPR rate for smokers, squamous cell histology, ChRT-surgery interval >65 days, and no-driver mutations. Multivariate analysis showed that only no-driver mutations (OR 0.39, p = 0.02) remained significant for MPR. PD-L1 status did not affect MPR. At 2 years, the driver mutation group had lower rates of local control (Hazard ration [HR] 0.67, p = 0.17) and disease-free survival (HR 0.5, p = 0.001). Overall survival was similar for both groups (HR = 1.04, p = 0.86).

CONCLUSION

Following 60 Gray NA-ChRT, tumors with a driver mutation had lower MPR and pCR rates than tumors without a driver mutation. PD-L1 was not associated with tumor regression.

ADVANCES IN KNOWLEDGE

Patients with resectable LA-NSCLC and an EGFR driver mutation treated with neoadjuvant-ChRT and completion surgery have reduced pathologic regression, lower local control rates, and shorter disease-free survival than patients without a driver mutation. Evaluation of molecular testing should be introduced in LA-NSCLC intended for prognostication and treatment decisions.

Single Cell Transcriptome in Colorectal Cancer-Current Updates on Its Application in Metastasis, Chemoresistance and the Roles of Circulating Tumor Cells

Colorectal cancer (CRC) is among the most common cancer worldwide, a challenge for research, and a model for studying the molecular mechanisms involved in its development. Previously, bulk transcriptomics analyses were utilized to classify CRC based on its distinct molecular and clinicopathological features for prognosis and diagnosis of patients. The introduction of single-cell transcriptomics completely turned the table by enabling the examination of the expression levels of individual cancer cell within a single tumor. In this review, we highlighted the importance of these single-cell transcriptomics analyses as well as suggesting circulating tumor cells (CTCs) as the main focus of single-cell RNA sequencing. Characterization of these cells might reveal the intratumoral heterogeneity present in CRC while providing critical insights into cancer metastasis. To summarize, we believed the analysis of gene expression patterns of CTC from CRC at single-cell resolution holds the potential to provide key information for identification of prognostic and diagnostic markers as well as the development of precise and personalized cancer treatment.

Chromosomal barcoding of E. coli populations reveals lineage diversity dynamics at high resolution

Evolutionary dynamics in large asexual populations is strongly influenced by multiple competing beneficial lineages, most of which segregate at very low frequencies. However, technical barriers to tracking a large number of these rare lineages in bacterial populations have so far prevented a detailed elucidation of evolutionary dynamics. Here, we overcome this hurdle by developing a chromosomal-barcoding technique that allows simultaneous tracking of approximately 450,000 distinct lineages in Escherichia coli, which we use to test the effect of sub-inhibitory concentrations of common antibiotics on the evolutionary dynamics of low-frequency lineages. We find that populations lose lineage diversity at distinct rates that correspond to their antibiotic regimen. We also determine that some lineages have similar fates across independent experiments. By analysing the trajectory dynamics, we attribute the reproducible fates of these lineages to the presence of pre-existing beneficial mutations, and we demonstrate how the relative contribution of pre-existing and de novo mutations varies across drug regimens. Finally, we reproduce the observed lineage dynamics by simulations. Altogether, our results provide a valuable methodology for studying bacterial evolution as well as insights into evolution under sub-inhibitory antibiotic levels.

Comparison between two different next generation sequencing platforms for clinical relevant gene mutation test in solid tumours

In the present study, we analysed 44 formalin fixed paraffin embedded (FFPE) from different solid tumours by adopting two different next generation sequencing platforms: GeneReader (QIAGEN, Hilden, Germany) and Ion Torrent (Thermo Fisher Scientific, Waltham, Massachusetts, USA). We highlighted a 100% concordance between the platforms. In addition, focusing on variant detection, we evaluated a very good agreement between the two tests (Cohen's kappa=0.84) and, when taking into account variant allele fraction value for each variant, a very high concordance was obtained (Pearson's r=0.94). Our results underlined the high performance rate of GeneReader on FFPE samples and its suitability in routine molecular predictive practice.

Development, Implementation and Assessment of Molecular Diagnostics by Next Generation Sequencing in Personalized Treatment of Cancer: Experience of a Public Reference Healthcare Hospital

The establishment of precision medicine in cancer patients requires the study of several biomarkers. Single-gene testing approaches are limited by sample availability and turnaround time. Next generation sequencing (NGS) provides an alternative for detecting genetic alterations in several genes with low sample requirements. Here we show the implementation to routine diagnostics of a NGS assay under International Organization for Standardization (UNE-EN ISO 15189:2013) accreditation. For this purpose, 106 non-small cell lung cancer (NSCLC) and 102 metastatic colorectal cancer (mCRC) specimens were selected for NGS analysis with Oncomine Solid Tumor (ThermoFisher). In NSCLC the most prevalently mutated gene was TP53 (49%), followed by KRAS (31%) and EGFR (13%); in mCRC, TP53 (50%), KRAS (48%) and PIK3CA (16%) were the most frequently mutated genes. Moreover, NGS identified actionable genetic alterations in 58% of NSCLC patients, and 49% of mCRC patients did not harbor primary resistance mechanisms to anti-EGFR treatment. Validation with conventional approaches showed an overall agreement >90%. Turnaround time and cost analysis revealed that NGS implementation is feasible in the public healthcare context. Therefore, NGS is a multiplexed molecular diagnostic tool able to overcome the limitations of current molecular diagnosis in advanced cancer, allowing an improved and economically sustainable molecular profiling.

Application of next-generation sequencing technology to precision medicine in cancer: joint consensus of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology

Next-generation sequencing (NGS) technology is capable of sequencing millions or billions of DNA molecules simultaneously. Therefore, it represents a promising tool for the analysis of molecular targets for the initial diagnosis of disease, monitoring of disease progression, and identifying the mechanism of drug resistance. On behalf of the Tumor Biomarker Committee of the Chinese Society of Clinical Oncology (CSCO) and the China Actionable Genome Consortium (CAGC), the present expert group hereby proposes advisory guidelines on clinical applications of NGS technology for the analysis of cancer driver genes for precision cancer therapy. This group comprises an assembly of laboratory cancer geneticists, clinical oncologists, bioinformaticians, pathologists, and other professionals. After multiple rounds of discussions and revisions, the expert group has reached a preliminary consensus on the need of NGS in clinical diagnosis, its regulation, and compliance standards in clinical sample collection. Moreover, it has prepared NGS criteria, the sequencing standard operation procedure (SOP), data analysis, report, and NGS platform certification and validation.

Tumor Tissue Explant Culture of Patient-Derived Xenograft as Potential Prioritization Tool for Targeted Therapy

Despite of remarkable progress made in the head and neck cancer (HNC) therapy, the survival rate of this metastatic disease remain low. Tailoring the appropriate therapy to patients is a major challenge and highlights the unmet need to have a good preclinical model that will predict clinical response. Hence, we developed an accurate and time efficient drug screening method of tumor ex vivo analysis (TEVA) system, which can predict patient-specific drug responses. In this study, we generated six patient derived xenografts (PDXs) which were utilized for TEVA. Briefly, PDXs were cut into 2 × 2 × 2 mm3 explants and treated with clinically relevant drugs for 24 h. Tumor cell proliferation and death were evaluated by immunohistochemistry and TEVA score was calculated. Ex vivo and in vivo drug efficacy studies were performed on four PDXs and three drugs side-by-side to explore correlation between TEVA and PDX treatment in vivo. Efficacy of drug combinations was also ventured. Optimization of the culture timings dictated 24 h to be the time frame to detect drug responses and drug penetrates 2 × 2 × 2 mm3 explants as signaling pathways were significantly altered. Tumor responses to drugs in TEVA, significantly corresponds with the drug efficacy in mice. Overall, this low cost, robust, relatively simple and efficient 3D tissue-based method, employing material from one PDX, can bypass the necessity of drug validation in immune-incompetent PDX-bearing mice. Our data provides a potential rationale for utilizing TEVA to predict tumor response to targeted and chemo therapies when multiple targets are proposed.

Simultaneous identification of clinically relevant single nucleotide variants, copy number alterations and gene fusions in solid tumors by targeted next-generation sequencing

In this study, we have set-up a routine pipeline to evaluate the clinical application of Oncomine™ Focus Assay, a panel that allows the simultaneous detection of single nucleotide hotspot mutations in 35 genes, copy number alterations (CNAs) in 19 genes and gene fusions involving 23 genes in cancer samples. For this study we retrospectively selected 106 patients that were submitted to surgical resection for lung, gastric, colon or rectal cancer.

We found that 56 patients out of 106 showed at least one alteration (53%), with 47 patients carrying at least one relevant nucleotide variant, 10 patients carrying at least one CNA and 3 patients carrying one gene fusion. On the basis of the mutational profiles obtained, we have identified 22 patients (20.7%) that were potentially eligible for targeted therapy.

The most frequently mutated genes across all tumor types included KRAS (30 patients), PIK3CA (16 patients), BRAF (6 patients), EGFR (5 patients), NRAS (4 patients) and ERBB2 (3 patients) whereas CCND1, ERBB2, EGFR and MYC were the genes most frequently subjected to copy number gain. Finally, gene fusions were identified only in lung cancer patients and involved MET [MET(13)–MET(15) fusion] and FGFR3 [FGFR3(chr 17)–TACC3(chr 11)].

In conclusion, we demonstrate that the analysis with a multi-biomarker panel of cancer patients after surgery, may present several potential advantages in clinical daily practice, including the simultaneous detection of different potentially druggable alterations, reasonable costs, short time of testing and automated interpretation of results.

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

Somatic Mutations Activating the mTOR Pathway in Dorsal Telencephalic Progenitors Cause a Continuum of Cortical Dysplasias

Focal cortical dysplasia (FCD) and hemimegalencephaly (HME) are epileptogenic neurodevelopmental malformations caused by mutations in mTOR pathway genes. Deep sequencing of these genes in FCD/HME brain tissue identified an etiology in 27 of 66 cases (41%). Radiographically indistinguishable lesions are caused by somatic activating mutations in AKT3, MTOR, and PIK3CA and germline loss-of-function mutations in DEPDC5, NPRL2, and TSC1/2, including TSC2 mutations in isolated HME demonstrating a "two-hit" model. Mutations in the same gene cause a disease continuum from FCD to HME to bilateral brain overgrowth, reflecting the progenitor cell and developmental time when the mutation occurred. Single-cell sequencing demonstrated mTOR activation in neurons in all lesions. Conditional Pik3ca activation in the mouse cortex showed that mTOR activation in excitatory neurons and glia, but not interneurons, is sufficient for abnormal cortical overgrowth. These data suggest that mTOR activation in dorsal telencephalic progenitors, in some cases specifically the excitatory neuron lineage, causes cortical dysplasia.

Single molecule sequencing of the M13 virus genome without amplification

Next generation sequencing (NGS) has revolutionized life sciences research. However, GC bias and costly, time-intensive library preparation make NGS an ill fit for increasing sequencing demands in the clinic. A new class of third-generation sequencing platforms has arrived to meet this need, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single-molecule sequencing platform from Direct Genomics to sequence the genome of the M13 virus. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. We sequenced the genome of M13 to a depth of 316x, with 100% coverage. We determined a consensus sequence accuracy of 100%. In contrast to GC bias inherent to NGS results, we demonstrated that our single-molecule sequencing method yields minimal GC bias.

Phenotype-driven precision oncology as a guide for clinical decisions one patient at a time

Genomics-driven cancer therapeutics has gained prominence in personalized cancer treatment. However, its utility in indications lacking biomarker-driven treatment strategies remains limited. Here we present a "phenotype-driven precision-oncology" approach, based on the notion that biological response to perturbations, chemical or genetic, in ex vivo patient-individualized models can serve as predictive biomarkers for therapeutic response in the clinic. We generated a library of "screenable" patient-derived primary cultures (PDCs) for head and neck squamous cell carcinomas that reproducibly predicted treatment response in matched patient-derived-xenograft models. Importantly, PDCs could guide clinical practice and predict tumour progression in two n = 1 co-clinical trials. Comprehensive "-omics" interrogation of PDCs derived from one of these models revealed YAP1 as a putative biomarker for treatment response and survival in ~24% of oral squamous cell carcinoma. We envision that scaling of the proposed PDC approach could uncover biomarkers for therapeutic stratification and guide real-time therapeutic decisions in the future.Treatment response in patient-derived models may serve as a biomarker for response in the clinic. Here, the authors use paired patient-derived mouse xenografts and patient-derived primary culture models from head and neck squamous cell carcinomas, including metastasis, as models for high-throughput screening of anti-cancer drugs.