Consensus on precision medicine for metastatic cancers: a report from the MAP conference

Genomic Profiling for Predictive Treatment Strategies in Fibrotic Interstitial Lung Disease

Idiopathic pulmonary fibrosis (IPF) has traditionally been considered the archetype of progressive fibrotic interstitial lung diseases (f-ILDs), but several other f-ILDs can also manifest a progressive phenotype. Integrating genomic signatures into clinical practice for f-ILD patients may help to identify patients predisposed to a progressive phenotype. In addition to the risk of progressive pulmonary fibrosis, there is a growing body of literature examining how pharmacogenomics influences treatment response, particularly regarding the efficacy and safety profiles of antifibrotic and immunomodulatory agents. In this narrative review, we discuss current studies in IPF and other forms of pulmonary fibrosis, including systemic autoimmune disorders associated ILDs, sarcoidosis and hypersensitivity pneumonitis. We also provide insights into the future direction of research in this complex field.

Prostate Cancer Lung Metastasis: Clinical Insights and Therapeutic Strategies

Prostate cancer lung metastasis represents a clinical conundrum due to its implications for advanced disease progression and the complexities it introduces in treatment planning. As the disease progresses to distant sites such as the lung, the clinical management becomes increasingly intricate, requiring tailored therapeutic strategies to address the unique characteristics of metastatic lesions. This review seeks to synthesize the current state of knowledge surrounding prostate cancer metastasis to the lung, shedding light on the diverse array of clinical presentations encountered, ranging from subtle radiological findings to overt symptomatic manifestations. By examining the diagnostic modalities utilized in identifying this metastasis, including advanced imaging techniques and histopathological analyses, this review aims to provide insights into the diagnostic landscape and the challenges associated with accurately characterizing lung metastatic lesions in prostate cancer patients. Moreover, this review delves into the nuances of therapeutic interventions employed in managing prostate cancer lung metastasis, encompassing systemic treatments such as hormonal therapies and chemotherapy, as well as metastasis-directed therapies including surgery and radiotherapy.

Precision medicine in the era of multi-omics: can the data tsunami guide rational treatment decision?

Precision medicine for cancer is rapidly moving to an approach that integrates multiple dimensions of the biology in order to model mechanisms of cancer progression in each patient. The discovery of multiple drivers per tumor challenges medical decision that faces several treatment options. Drug sensitivity depends on the actionability of the target, its clonal or subclonal origin and coexisting genomic alterations. Sequencing has revealed a large diversity of drivers emerging at treatment failure, which are potential targets for clinical trials or drug repurposing. To effectively prioritize therapies, it is essential to rank genomic alterations based on their proven actionability. Moving beyond primary drivers, the future of precision medicine necessitates acknowledging the intricate spatial and temporal heterogeneity inherent in cancer. The advent of abundant complex biological data will make artificial intelligence algorithms indispensable for thorough analysis. Here, we will discuss the advancements brought by the use of high-throughput genomics, the advantages and limitations of precision medicine studies and future perspectives in this field.

Integration of Next-Generation Sequencing in the Surgical Management of Colorectal Liver Metastasis

Hepatic resection remains the treatment of choice for colorectal liver metastases. The advancement of surgical technique and use of perioperative systemic therapy has expanded the number and complexity of patients eligible for surgical resection. In recent years, investigation into gene mutations, such as RAS/RAF pathway, have led to targeted therapies that have significantly improved outcomes. Next-generation sequencing allows analysis of large number of genes that may have potential prognostic relevance in the clinical setting. This review summarizes the current applications of next-generation sequencing technology in metastatic colorectal cancer, focusing on its prognostic implications on patient management.

A deformability-based biochip for precise label-free stratification of metastatic subtypes using deep learning

Cellular deformability is a promising biomarker for evaluating the physiological state of cells in medical applications. Microfluidics has emerged as a powerful technique for measuring cellular deformability. However, existing microfluidic-based assays for measuring cellular deformability rely heavily on image analysis, which can limit their scalability for high-throughput applications. Here, we develop a parallel constriction-based microfluidic flow cytometry device and an integrated computational framework (ATMQcD). The ATMQcD framework includes automatic training set generation, multiple object tracking, segmentation, and cellular deformability quantification. The system was validated using cancer cell lines of varying metastatic potential, achieving a classification accuracy of 92.4% for invasiveness assessment and stratifying cancer cells before and after hypoxia treatment. The ATMQcD system also demonstrated excellent performance in distinguishing cancer cells from leukocytes (accuracy = 89.5%). We developed a mechanical model based on power-law rheology to quantify stiffness, which was fitted with measured data directly. The model evaluated metastatic potentials for multiple cancer types and mixed cell populations, even under real-world clinical conditions. Our study presents a highly robust and transferable computational framework for multiobject tracking and deformation measurement tasks in microfluidics. We believe that this platform has the potential to pave the way for high-throughput analysis in clinical applications, providing a powerful tool for evaluating cellular deformability and assessing the physiological state of cells.

Comprehensive Genomic Profiling and Therapeutic Implications for Patients with Advanced Cancers: The Experience of an Academic Hospital

Next-generation sequencing (NGS) can be used to detect tumor-specific genomic alterations. This retrospective single-center study aims to assess the application of an extensive NGS panel to identify actionable alterations and initiate matched targeted treatment for patients with advanced cancer. We analyzed genomic alterations in solid tumor biopsies from 464 patients with advanced cancer with the Foundation Medicine assay (FoundationOne®CDx). Therapeutic implications were determined using the Memorial Sloan Kettering Precision Oncology Knowledge Base (OncoKB) classification. The FoundationOne®CDx was successfully applied in 464/521 patients (89%). The most common altered genes were TP53 (61%), KRAS (20%), CDKN2A (20%), TERT (16%), and APC (16%). Among the 419 patients with successfully analyzed tumor mutational burden (TMB), 43 patients presented with a high TMB (≥10 mutations/megabase). Out of the 126 patients with an actionable target, 40 patients received matched treatment (32%) of which 17 were within a clinical trial. This study shows that the application of NGS is feasible in an academic center and increases the detection of actionable alterations and identification of patients eligible for targeted treatment or immunotherapy regardless of tumor histology. Strategies such as early referral for NGS, inclusion in clinical (basket) trials, and the development of new targeted drugs are necessary to improve the matched treatment rate.

How to read a next-generation sequencing report—what oncologists need to know

Next-generation sequencing (NGS) of tumor cell-derived DNA/RNA to screen for targetable genomic alterations is now widely available and has become part of routine practice in oncology. NGS testing strategies depend on cancer type, disease stage and the impact of results on treatment selection. The European Society for Medical Oncology (ESMO) has recently published recommendations for the use of NGS in patients with advanced cancer. We complement the ESMO recommendations with a practical review of how oncologists should read and interpret NGS reports. A concise and straightforward NGS report contains details of the tumor sample, the technology used and highlights not only the most important and potentially actionable results, but also other pathogenic alterations detected. Variants of unknown significance should also be listed. Interpretation of NGS reports should be a joint effort between molecular pathologists, tumor biologists and clinicians. Rather than relying and acting on the information provided by the NGS report, oncologists need to obtain a basic level of understanding to read and interpret NGS results. Comprehensive annotated databases are available for clinicians to review the information detailed in the NGS report. Molecular tumor boards do not only stimulate debate and exchange, but may also help to interpret challenging reports and to ensure continuing medical education.

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NGS is routinely carried out in the diagnostic work-up of several cancer types.

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In many other malignancies NGS is carried out after exhaustion of standard therapy options.

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Minimal requirements for the NGS report are detailed in this review.

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Interpretation of NGS reports can be challenging and require interdisciplinary discussion.

Precision Oncology in Canada: Converting Vision to Reality with Lessons from International Programs

Canada's healthcare system, like others worldwide, is immersed in a process of evolution, attempting to adapt conventional frameworks of health technology assessment (HTA) and funding models to a new landscape of precision medicine in oncology. In particular, the need for real-world evidence in Canada is not matched by the necessary infrastructure and technologies required to integrate genomic and clinical data. Since healthcare systems in many developed nations face similar challenges, we adopted a solutions-based approach and conducted a search of worldwide programs in personalized medicine, with an emphasis on precision oncology. This search strategy included review articles published between 1 January 2016 and 1 March 2021 and hand-searches of their reference lists for relevant publications back to 1 December 2005. Thirty-nine initiatives across 37 countries in Europe, Australasia, Africa, and the Americas had the potential to lead to real-world data (RWD) on the clinical utility of oncology biomarkers. We highlight four initiatives with helpful lessons for Canada: Genomic Medicine France 2025, UNICANCER, the German Medical Informatics Initiative, and CANCER-ID. Among the 35 other programs evaluated, the main themes included the need for collaboration and systems to support data harmonization across multiple jurisdictions. In order to generate RWD in precision oncology that will prove acceptable to HTA bodies, Canada must take a national approach to biomarker strategy and unite all stakeholders at the highest level to overcome jurisdictional and technological barriers.

Frequently Expressed Glypican-3 As A Promising Novel Therapeutic Target for Osteosarcomas

Osteosarcoma (OS) is the most common bone malignancy without a reliable therapeutic target. Glypican-3 (GPC3) mutation and upregulation have been detected in multi-drug resistant OS, and anti-GPC3 immunotherapy can effectively suppress the growth of organoids. Further profiling of GPC3 mutations and expression patterns in OS is of clinical significance. To address these issues, fresh OS specimens were collected from 24 patients for cancer-targeted next-generation sequencing (NGS) and three-dimensional patient-derived organoid (PDO) culture. A tumor microarray was prepared using 37 archived OS specimens. Immunohistochemical (IHC) staining was performed on OS specimens and microarrays to profile GPC3 and CD133 expression as well as intratumoral distribution patterns. RT-PCR was conducted to semi-quantify GPC3 and CD133 expression levels in the OS tissues. Anti-GPC3 immunotherapy was performed on OS organoids with or without GPC3 expression and its efficacy was analyzed using multiple experimental approaches. No OS cases with GPC3 mutations were found, except for the positive control (OS-08). IHC staining revealed GPC3 expression in 73.77% (45/61) of OSs in weak (+; 29/45), moderate (++; 8/45), and strong (+++; 8/45) immunolabeling densities. The intratumoral distribution of GPC3-positive cells was variable in the focal (+; 10-30%; 8/45), partial (++; 31-70%; 22/45), and the most positive patterns (+++; > 71%; 15/45), which coincided with CD133 immunolabeling (P = 9.89×10^-10 ). The anti-GPC3 antibody efficiently inhibits Wnt/β-catenin signaling and induces apoptosis in GPC3-positive PDOs and PDXs, as opposed to GPC3-negative PDOs and PDXs. The high frequency of GPC3 and CD133 co-expression and the effectiveness of anti-wildtype GPC3-ab therapy in GPC3-positive OS models suggest that GPC3 is a novel prognostic parameter and a promising therapeutic target for osteosarcoma.

Genomic Features of Lung-Recurrent Hormone-Sensitive Prostate Cancer

PURPOSE

Pulmonary involvement is rare in metastatic hormone-sensitive prostate cancer (mHSPC) that recurs after treatment for localized disease. Guidelines recommend intensive systemic therapy, similar to patients with liver metastases, but some lung-recurrent mHSPC may have good outcomes. Genomic features of lung metastases may clarify disease aggression, but are poorly understood since lung biopsy is rarely performed. We present a comparative assessment of genomic drivers and heterogeneity in metachronous prostate tumors and lung metastases.

METHODS

We leveraged a prospective functional imaging study of 208 biochemically recurrent prostate cancers to identify 10 patients with lung-recurrent mHSPC. Histologic diagnosis was attained via thoracic surgery or fine-needle lung biopsy. We retrieved clinical data and performed multiregion sampling of primary tumors and metastases. Targeted and/or whole-exome sequencing was applied to 46 primary and 32 metastatic foci.

RESULTS

Unusually for mHSPC, all patients remained alive despite a median follow-up of 11.5 years. Several patients experienced long-term freedom from systemic treatment. The genomic landscape of lung-recurrent mHSPC was typical of curable prostate cancer with frequent PTEN, SPOP, and chromosome 8p alterations, and there were no deleterious TP53 and DNA damage repair gene mutations that characterize aggressive prostate cancer. Despite a long median time to recurrence (76.8 months), copy number alterations and clonal mutations were highly conserved between metastatic and primary foci, consistent with intrapatient homogeneity and limited genomic evolution.

CONCLUSION

In this retrospective hypothesis-generating study, we observed indolent genomic etiology in selected lung-recurrent mHSPC, cautioning against grouping these patients together with liver or bone-predominant mHSPC. Although our data do not generalize to all patients with lung metastases, the results encourage prospective efforts to stratify lung-recurrent mHSPC by genomic features.

Progress of targeted and immunotherapy for hepatocellular carcinoma and the application of next-generation sequencing

Hepatocellular carcinoma (HCC), leading cancer worldwide, has a high degree of genetic heterogeneity; next-generation sequencing (NGS) technology has contributed significantly to the discovery of driving genes as well as high-frequency mutations in HCC. The detection of gene alterations may allow us to predict prognosis and adverse drug reactions for individuals, paving the way for personalized medicine in HCC patients. In this review, we summarized the common systemic therapy regimens for HCC and the predictive efficacy of genetic biomarkers on the prognosis of patients under these treatments. Finally, we put forward a future perspective on the potential of NGS technology for the guidance of targeted therapy and immunotherapy in HCC.

The emerging roles of NGS in clinical oncology and personalized medicine

Next-generation sequencing (NGS) has been increasingly popular in genomics studies over the last decade, as new sequencing technology has been created and improved. Recently, NGS started to be used in clinical oncology to improve cancer therapy through diverse modalities ranging from finding novel and rare cancer mutations, discovering cancer mutation carriers to reaching specific therapeutic approaches known as personalized medicine (PM). PM has the potential to minimize medical expenses by shifting the current traditional medical approach of treating cancer and other diseases to an individualized preventive and predictive approach. Currently, NGS can speed up in the early diagnosis of diseases and discover pharmacogenetic markers that help in personalizing therapies. Despite the tremendous growth in our understanding of genetics, NGS holds the added advantage of providing more comprehensive picture of cancer landscape and uncovering cancer development pathways. In this review, we provided a complete overview of potential NGS applications in scientific and clinical oncology, with a particular emphasis on pharmacogenomics in the direction of precision medicine treatment options.

Identification of GPC3 mutation and upregulation in a multidrug resistant osteosarcoma and its spheroids as therapeutic target

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GPC3 mutation in primary osteosarcoma becomes abundant in its metastasis.

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Mutant GPC3 is over-produced in metastatic spheroids with multidrug resistance.

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Anti-GPC3 antibody effectively commits metastatic spheroids to apoptosis.

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GPC3 would be a promising therapeutic target of osteosarcomas.

Background

Drug resistance and the lack of molecular therapeutic target are the main challenges in the management of osteosarcomas (OSs). Identification of novel genetic alteration(s) related with OS recurrence and chemotherapeutic resistance would be of scientific and clinical significance.

Methods

To identify potential genetic alterations related with OS recurrence and chemotherapeutic resistance, the biopsies of a 20-year-old male osteosarcoma patient were collected at primary site (p-OS) and from its metastatic tumor (m-OS) formed after 5 months of adjuvant chemotherapy. Both OS specimens were subjected to cancer-targeted next generation sequencing (NGS) and their cell suspensions were cultured under three-dimensional condition to establish spheroid therapeutic model. Transcript-oriented Sanger sequencing for GPC3, the detected mutated gene, was performed on RNA samples of p-OS and m-OS tissues and spheroids. The effects of anti-GPC3 antibody and its combination with cisplatin on m-OS spheroids were elucidated.

Results

NGS revealed 4 mutations (GPC3, SOX10, MDM4 and MAPK8) and 6 amplifications (MDM2, CDK4, CCND3, RUNX2, GLI1 and FRS2) in p-OS, and 3 mutations (GPC3, SOX10 and EGF) and 10 amplifications (CDK4, CCND3, MDM2, RUNX2, GLI1, FRS2, CARD11, RAC1, SLC16A7 and PMS2) in m-OS. Among those alterations, the mutation abundance of GPC3 was the highest (56.49%) in p-OS and showed 1.54 times increase in m-OS. GPC3 transcript-oriented Sanger sequencing confirmed the mutation at 1046 in Exon 4, and immunohistochemical staining showed increased GPC3 production in m-OS tissues and its spheroids. EdU cell proliferation and Calcein/PI cell viability assays revealed that of the anti-OS first line drugs (doxorubicin, cisplatin, methotrexate, ifosfamide and carboplatin), 10 μM carboplatin exerted the best inhibitory effects on the p-OS but not the m-OS spheroids. 2 μg/mL anti-GPC3 antibody effectively committed m-OS spheroids to death by itself (76.43%) or in combination with cisplatin (92.93%).

Conclusion

This study demonstrates increased abundance and up-regulated expression of mutant GPC3 in metastatic osteosarcoma and its spheroids with multidrug resistance. As GPC3-targeting therapy has been used to treat hepatocellular carcinomas and it is also effective to OS PDSs, GPC3 would be a novel prognostic parameter and therapeutic target of osteosarcomas.

Homologous Recombination Deficiency in Pancreatic Cancer: A Systematic Review and Prevalence Meta-Analysis

PURPOSE

To analyze the prevalence of homologous recombination deficiency (HRD) in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

We conducted a systematic review and meta-analysis of the prevalence of HRD in PDAC from PubMed, Scopus, and Cochrane Library databases, and online cancer genomic data sets. The main outcome was pooled prevalence of somatic and germline mutations in the better characterized HRD genes (BRCA1, BRCA2, PALB2, ATM, ATR, CHEK2, RAD51, and the FANC genes). The secondary outcomes were prevalence of germline mutations overall, and in sporadic and familial cases; prevalence of germline BRCA1/2 mutations in Ashkenazi Jewish (AJ); and prevalence of HRD based on other definitions (ie, alterations in other genes, genomic scars, and mutational signatures). Random-effects modeling with the Freeman-Tukey transformation was used for the analyses. PROSPERO registration number: (CRD42020190813).

RESULTS

Sixty studies with 21,842 participants were included in the systematic review and 57 in the meta-analysis. Prevalence of germline and somatic mutations was BRCA1: 0.9%, BRCA2: 3.5%, PALB2: 0.2%, ATM: 2.2%, CHEK2: 0.3%, FANC: 0.5%, RAD51: 0.0%, and ATR: 0.1%. Prevalence of germline mutations was BRCA1: 0.9% (2.4% in AJ), BRCA2: 3.8% (8.2% in AJ), PALB2: 0.2%, ATM: 2%, CHEK2: 0.3%, and FANC: 0.4%. No significant differences between sporadic and familial cases were identified. HRD prevalence ranged between 14.5%-16.5% through targeted next-generation sequencing and 24%-44% through whole-genome or whole-exome sequencing allowing complementary genomic analysis, including genomic scars and other signatures (surrogate markers of HRD).

CONCLUSION

Surrogate readouts of HRD identify a greater proportion of patients with HRD than analyses limited to gene-level approaches. There is a clear need to harmonize HRD definitions and to validate the optimal biomarker for treatment selection. Universal HRD screening including integrated somatic and germline analysis should be offered to all patients with PDAC.

Prospective high-throughput genome profiling of advanced cancers: results of the PERMED-01 clinical trial

BACKGROUND

The benefit of precision medicine based on relatively limited gene sets and often-archived samples remains unproven. PERMED-01 (NCT02342158) was a prospective monocentric clinical trial assessing, in adults with advanced solid cancer, the feasibility and impact of extensive molecular profiling applied to newly biopsied tumor sample and based on targeted NGS (t-NGS) of the largest gene panel to date and whole-genome array-comparative genomic hybridization (aCGH) with assessment of single-gene alterations and clinically relevant genomic scores.

METHODS

Eligible patients with refractory cancer had one tumor lesion accessible to biopsy. Extracted tumor DNA was profiled by t-NGS and aCGH. We assessed alterations of 802 "candidate cancer" genes and global genomic scores, such as homologous recombination deficiency (HRD) score and tumor mutational burden. The primary endpoint was the number of patients with actionable genetic alterations (AGAs). Secondary endpoints herein reported included a description of patients with AGA who received a "matched therapy" and their clinical outcome, and a comparison of AGA identification with t-NGS and aCGH versus whole-exome sequencing (WES).

RESULTS

Between November 2014 and September 2019, we enrolled 550 patients heavily pretreated. An exploitable complete molecular profile was obtained in 441/550 patients (80%). At least one AGA, defined in real time by our molecular tumor board, was found in 393/550 patients (71%, two-sided 90%CI 68-75%). Only 94/550 patients (17%, 95%CI 14-21) received an "AGA-matched therapy" on progression. The most frequent AGAs leading to "matched therapy" included PIK3CA mutations, KRAS mutations/amplifications, PTEN deletions/mutations, ERBB2 amplifications/mutations, and BRCA1/2 mutations. Such "matched therapy" improved by at least 1.3-fold the progression-free survival on matched therapy (PFS2) compared to PFS on prior therapy (PFS1) in 36% of cases, representing 6% of the enrolled patients. Within patients with AGA treated on progression, the use of "matched therapy" was the sole variable associated with an improved PFS2/PFS1 ratio. Objective responses were observed in 19% of patients treated with "matched therapy," and 6-month overall survival (OS) was 62% (95%CI 52-73). In a subset of 112 metastatic breast cancers, WES did not provide benefit in term of AGA identification when compared with t-NGS/aCGH.

CONCLUSIONS

Extensive molecular profiling of a newly biopsied tumor sample identified AGA in most of cases, leading to delivery of a "matched therapy" in 17% of screened patients, of which 36% derived clinical benefit. WES did not seem to improve these results.

TRIAL REGISTRATION

ID-RCB identifier: 2014-A00966-41; ClinicalTrials.gov identifier: NCT02342158 .

Unique k-mer sequences for validating cancer-related substitution, insertion and deletion mutations

Cancer genome sequencing has led to important discoveries such as the identification of cancer genes. However, challenges remain in the analysis of cancer genome sequencing. One significant issue is that mutations identified by multiple variant callers are frequently discordant even when using the same genome sequencing data. For insertion and deletion mutations, oftentimes there is no agreement among different callers. Identifying somatic mutations involves read mapping and variant calling, a complicated process that uses many parameters and model tuning. To validate the identification of true mutations, we developed a method using k-mer sequences. First, we characterized the landscape of unique versus non-unique k-mers in the human genome. Second, we developed a software package, KmerVC, to validate the given somatic mutations from sequencing data. Our program validates the occurrence of a mutation based on statistically significant difference in frequency of k-mers with and without a mutation from matched normal and tumor sequences. Third, we tested our method on both simulated and cancer genome sequencing data. Counting k-mer involving mutations effectively validated true positive mutations including insertions and deletions across different individual samples in a reproducible manner. Thus, we demonstrated a straightforward approach for rapidly validating mutations from cancer genome sequencing data.

Development of synthetic lethality in cancer: molecular and cellular classification

Recently, genetically targeted cancer therapies have been a topic of great interest. Synthetic lethality provides a new approach for the treatment of mutated genes that were previously considered unable to be targeted in traditional genotype-targeted treatments. The increasing researches and applications in the clinical setting made synthetic lethality a promising anticancer treatment option. However, the current understandings on different conditions of synthetic lethality have not been systematically assessed and the application of synthetic lethality in clinical practice still faces many challenges. Here, we propose a novel and systematic classification of synthetic lethality divided into gene level, pathway level, organelle level, and conditional synthetic lethality, according to the degree of specificity into its biological mechanism. Multiple preclinical findings of synthetic lethality in recent years will be reviewed and classified under these different categories. Moreover, synthetic lethality targeted drugs in clinical practice will be briefly discussed. Finally, we will explore the essential implications of this classification as well as its prospects in eliminating existing challenges and the future directions of synthetic lethality.

When should we order a next generation sequencing test in a patient with cancer?

Technical advances in genome sequencing and the implementation of next-generation sequencing (NGS) in clinical oncology have paved the way for individualizing cancer patient therapy based on molecular profiles. When and how to use NGS testing in the clinic is at present an unsolved issue, although new research results provide evidence favoring this approach in some types of advanced cancer. Clinical research is evolving rapidly, from basket and umbrella trials to adaptative design precision oncology clinical studies, and genomic and molecular data often displace the classical clinical validation procedures of biomarkers. In this context, physicians must be aware of the clinical evidence behind these new biomarkers and NGS tests available, in order to use them in the right moment, and with a critical point of view. This review will present the status of currently available targeted drugs that can be effective based on actionable molecular alterations, and the NGS tests that are currently available, offering a practical guide for the application of Clinical Precision Oncology in the real world routine practice.

A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic

PURPOSE

Dynamic network models predict clinical prognosis and inform therapeutic intervention by elucidating disease-driven aberrations at the systems level. However, the personalization of model predictions requires the profiling of multiple model inputs, which hampers clinical translation.

PATIENTS AND METHODS

We applied APOPTO-CELL, a prognostic model of apoptosis signaling, to showcase the establishment of computational platforms that require a reduced set of inputs. We designed two distinct and complementary pipelines: a probabilistic approach to exploit a consistent subpanel of inputs across the whole cohort (Ensemble) and a machine learning approach to identify a reduced protein set tailored for individual patients (Tree). Development was performed on a virtual cohort of 3,200,000 patients, with inputs estimated from clinically relevant protein profiles. Validation was carried out in an in-house stage III colorectal cancer cohort, with inputs profiled in surgical resections by reverse phase protein array (n = 120) and/or immunohistochemistry (n = 117).

RESULTS

Ensemble and Tree reproduced APOPTO-CELL predictions in the virtual patient cohort with 92% and 99% accuracy while decreasing the number of inputs to a consistent subset of three proteins (40% reduction) or a personalized subset of 2.7 proteins on average (46% reduction), respectively. Ensemble and Tree retained prognostic utility in the in-house colorectal cancer cohort. The association between the Ensemble accuracy and prognostic value (Spearman ρ = 0.43; P = .02) provided a rationale to optimize the input composition for specific clinical settings. Comparison between profiling by reverse phase protein array (gold standard) and immunohistochemistry (clinical routine) revealed that the latter is a suitable technology to quantify model inputs.

CONCLUSION

This study provides a generalizable framework to optimize the development of network-based prognostic assays and, ultimately, to facilitate their integration in the routine clinical workflow.

Clinical Relevance and Therapeutic Application of CTCs in Advanced Breast Cancer

Precision medicine through liquid biopsy represents an emerging approach in the management of cancer. The CTC count in blood samples from patients with advanced breast cancer is a powerful prognostic factor for both progression free and overall survival. Moreover, high levels of CTCs at any time during the treatment can reliably predict progression before imaging studies and/or tumor markers. Furthermore, there are works on the molecular characterization of the CTCs and their potential ability to guide the treatment in a dynamic way. However, their role remains controversial. Detection and enumeration of CTCs is variable among different tumors and is subjected to biases related mainly to their methodology, which is not completely standardized. In addition, they must demonstrate their clinical value to guide the treatment and a translation on patient's survival.

Concordance of Genomic Variants in Matched Primary Breast Cancer, Metastatic Tumor, and Circulating Tumor DNA: The MIRROR Study

PURPOSE

Genetic heterogeneity between primary tumors and their metastatic lesions has been documented in several breast cancer studies. However, the selection of therapy for patients with metastatic breast cancer and the search for biomarkers for targeted therapy are often based on findings from the primary tumor, mainly because of the difficulty of distant metastasis core biopsies. New methods for monitoring genomic changes in metastatic breast cancer are needed (ie, circulating tumor DNA [ctDNA] genomic analysis). The objectives of this study were to assess the concordance of genomic variants between primary and metastatic tumor tissues and the sensitivity of plasma ctDNA analysis to identify variants detected in tumor biopsies.

PATIENTS AND METHODS

Next-generation sequencing technology was used to assess the genomic mutation profile of a panel of 54 cancer genes in matched samples of primary tumor, metastatic tumor, and plasma from 40 patients with metastatic breast cancer.

RESULTS

Using Ion Torrent technology (ThermoFisher Scientific, Waltham, MA), we identified 110 variants that were common to the primary and metastatic tumors. ctDNA analysis had a sensitivity of 0.972 in detecting variants present in both primary and metastatic tissues. In addition, we identified 13 variants in metastatic tissue and ctDNA not present in primary tumor.

CONCLUSION

We identified genomic variants present in metastatic biopsies and plasma ctDNA that were not present in the primary tumor. Deep sequencing of plasma ctDNA detected most DNA variants previously identified in matched primary and metastatic tissues. ctDNA might aid in therapy selection and in the search for biomarkers for drug development in metastatic breast cancer.

Efficacy of PI3K inhibitors in advanced breast cancer

The phosphoinositide 3 (PI3)-kinase/Akt signaling pathway has always been a focus of interest in breast cancer due to its role in cell growth, cell proliferation, cell migration and deregulated apoptosis. Its activation has been linked to endocrine resistance and worse prognosis in certain subgroups of breast cancer. In addition, deregulation of the PI3K/Akt pathway including PIK3CA activating mutation is frequently present in breast cancer. Multiple efforts have been carried out to target this pathway, initially with pan-PI3K inhibitors with some hint of activity but hampered by their limiting side-effects. A recent large randomized trial in patients with endocrine-resistant PIK3CA-mutant hormone receptor (HR)-positive tumors led to the approval of the first PI3K inhibitor, alpelisib, in combination with fulvestrant. The specificity of alpelisib against the p110α catalytic isoform provided additional efficacy and a better toxicity profile. In this review, we summarize the main research with PI3K inhibitors in breast cancer and we provide some insight of potential future combinations of this treatment in breast cancer patients.

Bulk and Single-Cell Next-Generation Sequencing: Individualizing Treatment for Colorectal Cancer

The increasing incidence combined with constant rates of early diagnosis and mortality of colorectal cancer (CRC) over the past decade worldwide, as well as minor overall survival improvements in the industrialized world, suggest the need to shift from conventional research and clinical practice to the innovative development of screening, predictive and therapeutic tools. Explosive integration of next-generation sequencing (NGS) systems into basic, translational and, more recently, basket trials is transforming biomedical and cancer research, aiming for substantial clinical implementation as well. Shifting from inter-patient tumor variability to the precise characterization of intra-tumor genetic, genomic and transcriptional heterogeneity (ITH) via multi-regional bulk tissue NGS and emerging single-cell transcriptomics, coupled with NGS of circulating cell-free DNA (cfDNA), unravels novel strategies for therapeutic response prediction and drug development. Remarkably, underway and future genomic/transcriptomic studies and trials exploring spatiotemporal clonal evolution represent most rational expectations to discover novel prognostic, predictive and therapeutic tools. This review describes latest advancements and future perspectives of integrated sequencing systems for genome and transcriptome exploration to overcome unmet research and clinical challenges towards Precision Oncology.

Comprehensive intra-individual genomic and transcriptional heterogeneity: Evidence-based Colorectal Cancer Precision Medicine

Despite advances in translating conventional research into multi-modal treatment for colorectal cancer (CRC), therapeutic resistance and relapse remain unresolved in advanced resectable and, particularly, non-resectable disease. Genome and transcriptome sequencing and editing technologies, coupled with interaction mapping and machine learning, are transforming biomedical research, representing the most rational hope to overcome unmet research and clinical challenges. Rapid progress in both bulk and single-cell next-generation sequencing (NGS) analyses in the identification of primary and metastatic intratumor genomic and transcriptional heterogeneity (ITH) and the detection of circulating cell-free DNA (cfDNA) alterations is providing critical insight into the origins and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Moreover, DNA and RNA editing pave new avenues towards the discovery of novel drug targets. Breakthrough combinations of sequencing and editing systems with technologies exploring dynamic interaction networks within pioneering studies could delineate how coding and non-coding mutations perturb regulatory networks and gene expression. This review discusses latest data on genomic and transcriptomic landscapes in time and space, as well as early-phase clinical trials on targeted drug combinations, highlighting the transition from research to clinical Colorectal Cancer Precision Medicine, through non-invasive screening, individualized drug response prediction and development of multiple novel drugs. Future studies exploring the potential to target key transcriptional drivers and regulators will contribute to the next-generation pharmaceutical controllability of multi-layered aberrant transcriptional biocircuits.

A Phase II Randomized Study of Neoadjuvant Letrozole Plus Alpelisib for Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative Breast Cancer (NEO-ORB)

PURPOSE

Addition of alpelisib to fulvestrant significantly extended progression-free survival in PIK3CA-mutant, hormone receptor-positive (HR+) advanced/metastatic breast cancer in the phase III SOLAR-1 study. The combination of alpelisib and letrozole also had promising activity in phase I studies of HR+ advanced/metastatic breast cancer. NEO-ORB aimed to determine whether addition of alpelisib to letrozole could increase response rates in the neoadjuvant setting.Patients and Methods: Postmenopausal women with HR+, human epidermal growth factor receptor 2-negative, T1c-T3 breast cancer were assigned to the PIK3CA-wild-type or PIK3CA-mutant cohort according to their tumor PIK3CA status, and randomized (1:1) to 2.5 mg/day letrozole with 300 mg/day alpelisib or placebo for 24 weeks. Primary endpoints were objective response rate (ORR) and pathologic complete response (pCR) rate for both PIK3CA cohorts.

RESULTS

In total, 257 patients were assigned to letrozole plus alpelisib (131 patients) or placebo (126 patients). Grade ≥3 adverse events (≥5% of patients) in the alpelisib arm were hyperglycemia (27%), rash (12%), and maculo-papular rash (8%). The primary objective was not met; ORR in the alpelisib versus placebo arm was 43% versus 45% and 63% versus 61% in the PIK3CA-mutant and wild-type cohorts, respectively. pCR rates were low in all groups. Decreases in Ki-67 were similar across treatment arms and cohorts. In PIK3CA-mutant tumors, alpelisib plus letrozole treatment induced a greater decrease in phosphorylated AKT versus placebo plus letrozole.

CONCLUSIONS

In contrast to initial results in advanced/metastatic disease, addition of alpelisib to 24-week neoadjuvant letrozole treatment did not improve response in patients with HR+ early breast cancer.

Molecular subtypes of pancreatic cancer

Cancers that appear morphologically similar often have dramatically different clinical features, respond variably to therapy and have a range of outcomes. Compelling evidence now demonstrates that differences in the molecular pathology of otherwise indistinguishable cancers substantially impact the clinical characteristics of the disease. Molecular subtypes now guide preclinical and clinical therapeutic development and treatment in many cancer types. The ability to predict optimal therapeutic strategies ahead of treatment improves overall patient outcomes, minimizing treatment-related morbidity and cost. Although clinical decision making based on histopathological criteria underpinned by robust data is well established in many cancer types, subtypes of pancreatic cancer do not currently inform treatment decisions. However, accumulating molecular data are defining subgroups in pancreatic cancer with distinct biology and potential subtype-specific therapeutic vulnerabilities, providing the opportunity to define a de novo clinically applicable molecular taxonomy. This Review summarizes current knowledge concerning the molecular subtyping of pancreatic cancer and explores future strategies for using a molecular taxonomy to guide therapeutic development and ultimately routine therapy with the overall goal of improving outcomes for this disease.

Complexity of genome sequencing and reporting: Next generation sequencing (NGS) technologies and implementation of precision medicine in real life

The finalization of the Human Genome Project in 2003 paved the way for a deeper understanding of cancer, favouring a faster progression towards "personalized" medicine. Research in oncology has progressively focused on the sequencing of cancer genomes, to better understand the genetic basis of tumorigenesis and identify actionable alterations to guide cancer therapy. Thanks to the development of next-generation-sequencing (NGS) techniques, sequencing of tumoral DNA is today technically easier, faster and cheaper. Commercially available NGS panels enable the detection of single or global genomic alterations, namely gene mutation and mutagenic burden, both on germline and somatic DNA, potentially predicting the response or resistance to cancer treatments. Profiling of tumor DNA is nowadays a standard in cancer research and treatment. In this review we discuss the history, techniques and applications of NGS in cancer care, under a "personalized tailored therapy" perspective.

Dynamic genome and transcriptional network-based biomarkers and drugs: precision in breast cancer therapy

Despite remarkable progress in medium-term overall survival benefit in the adjuvant, neoadjuvant and metastatic settings, with multiple recent targeted drug approvals, acquired resistance, late relapse, and cancer-related death rates remain challenging. Integrated technological systems have been developed to overcome these unmet needs. The characterization of structural and functional noncoding genome elements through next-generation sequencing (NGS) systems, Hi-C and CRISPR/Cas9, as well as computational models, allows for whole genome and transcriptome analysis. Rapid progress in large-scale single-biopsy genome analysis has identified several novel breast cancer driver genes and oncotargets. The exploration of spatiotemporal tumor evolution has returned exciting while inconclusive data on dynamic intratumor heterogeneity (ITH) through multiregional NGS and single-cell DNA/RNA sequencing and circulating genomic subclones (cGSs) by serial circulating cell-free DNA NGS to predict and overcome intrinsic and acquired therapeutic resistance. This review discusses reliable breast cancer genome analysis data and focuses on two major crucial perspectives. The validation of ITH, cGSs, and intrapatient genetic/genomic heterogeneity as predictive biomarkers, as well as the valid discovery of novel oncotargets within patient-centric genomic trials, encouraging early drug development, could optimize primary and secondary therapeutic decision-making. A longer-term goal is to identify the individualized landscape of both coding and noncoding key mutations. This progress will enable the understanding of molecular mechanisms perturbating regulatory networks, shaping the pharmaceutical controllability of deregulated transcriptional biocircuits.

Precision Trial Drawer, a Computational Tool to Assist Planning of Genomics-Driven Trials in Oncology

Purpose

Trials that accrue participants on the basis of genetic biomarkers are a powerful means of testing targeted drugs, but they are often complicated by the rarity of the biomarker-positive population. Umbrella trials circumvent this by testing multiple hypotheses to maximize accrual. However, bigger trials have higher chances of conflicting treatment allocations because of the coexistence of multiple actionable alterations; allocation strategies greatly affect the efficiency of enrollment and should be carefully planned on the basis of relative mutation frequencies, leveraging information from large sequencing projects.

Methods

We developed software named Precision Trial Drawer (PTD) to estimate parameters that are useful for designing precision trials, most importantly, the number of patients needed to molecularly screen (NNMS) and the allocation rule that maximizes patient accrual on the basis of mutation frequency, systematically assigning patients with conflicting allocations to the drug associated with the rarer mutation. We used data from The Cancer Genome Atlas to show their potential in a 10-arm imaginary trial of multiple cancers on the basis of genetic alterations suggested by the past Molecular Analysis for Personalised Therapy (MAP) conference. We validated PTD predictions versus real data from the SHIVA (A Randomized Phase II Trial Comparing Therapy Based on Tumor Molecular Profiling Versus Conventional Therapy in Patients With Refractory Cancer) trial.

Results

In the MAP imaginary trial, PTD-optimized allocation reduces number of patients needed to molecularly screen by up to 71.8% (3.5 times) compared with nonoptimal trial designs. In the SHIVA trial, PTD correctly predicted the fraction of patients with actionable alterations (33.51% [95% CI, 29.4% to 37.6%] in imaginary v 32.92% [95% CI, 28.2% to 37.6%] expected) and allocation to specific treatment groups (RAS/MEK, PI3K/mTOR, or both).

Conclusion

PTD correctly predicts crucial parameters for the design of multiarm genetic biomarker-driven trials. PTD is available as a package in the R programming language and as an open-access Web-based app. It represents a useful resource for the community of precision oncology trialists. The Web-based app is available at https://gmelloni.github.io/ptd/shinyapp.html .

Emerging targets in advanced non-small-cell lung cancer

New therapeutic options in non-small-cell lung cancer have been available through a great in-depth and genomic research, improving preclinical disease patterns and identifying the specific toxicity of target therapy. The multidisciplinary approach, increasingly practiced among clinicians, researchers, pharmaceutical companies and ethics committees has allowed the emergence of a new generation of translational clinical trials and the adoption of new technologies (e.g., point-of-care sequencing), then speeding up the development and trade of these new drugs. Consequently, there is a long list of therapeutic candidates that need to be efficiently evaluated early in the context of Phase I clinical trials. In this review, we discuss some of the key developments and novelties in the main histological groups.

Copenhagen Prospective Personalized Oncology (CoPPO)-Clinical Utility of Using Molecular Profiling to Select Patients to Phase I Trials

PURPOSE

We evaluated the clinical benefit of tumor molecular profiling to select treatment in the phase I setting.

EXPERIMENTAL DESIGN

Patients with advanced solid cancers and exhausted treatment options referred to a phase I unit were included in a prospective, single-center, single-arm open-label study (NCT02290522). Tumor biopsies were obtained for comprehensive genomic analysis including whole-exome sequencing and RNA sequencing. When possible, patients were treated with regimen matched to the genomic profile. Primary endpoint was progression-free survival (PFS).

RESULTS

From May 2013 to January 2017, a total of 591 patients were enrolled, with 500 patients undergoing biopsy. Genomic profiles were obtained in 460 patients and a potential actionable target was identified in 352 (70%) of 500 biopsied patients. A total of 101 patients (20%) received matched treatment based on either gene mutations or RNA expression levels of targets available in early clinical trials or off-label treatment. Objective response according to RECIST1.1 was observed in 15 of 101 patients (0% complete response, 15% partial response), with a median PFS of 12 weeks (95% confidence interval, 9.9-14.4).

CONCLUSIONS

Our study supports the feasibility of genomic profiling to select patients in the phase I setting and suggests that genomic matching can be beneficial for a minor subset of patients with no other treatment options. Randomized studies may validate this assumption.See related commentary by Ratain, p. 1136.

Host and Viral Genetic Variation in HBV-Related Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer in men and the second leading cause of cancer deaths globally. The high prevalence of HCC is due in part to the high prevalence of chronic HBV infection and the high mortality rate is due to the lack of biomarkers for early detection and limited treatment options for late stage HCC. The observed individual variance in development of HCC is attributable to differences in HBV genotype and mutations, host predisposing germline genetic variations, the acquisition of tumor-specific somatic mutations, as well as environmental factors. HBV genotype C and mutations in the preS, basic core promoter (BCP) or HBx regions are associated with an increased risk of HCC. Genome-wide association studies have identified common polymorphisms in KIF1B, HLA-DQ, STAT4, and GRIK1 with altered risk of HBV-related HCC. HBV integration into growth control genes (such as TERT), pro-oncogenic genes, or tumor suppressor genes and the oncogenic activity of truncated HBx promote hepatocarcinogenesis. Somatic mutations in the TERT promoter and classic cancer signaling pathways, including Wnt (CTNNB1), cell cycle regulation (TP53), and epigenetic modification (ARID2 and MLL4) are frequently detected in hepatic tumor tissues. The identification of HBV and host variation associated with tumor initiation and progression has clinical utility for improving early diagnosis and prognosis; whereas the identification of somatic mutations driving tumorigenesis hold promise to inform precision treatment for HCC patients.

Biomarkers in breast cancer: A consensus statement by the Spanish Society of Medical Oncology and the Spanish Society of Pathology

This consensus statement revises and updates the recommendations for biomarkers use in the diagnosis and treatment of breast cancer, and is a joint initiative of the Spanish Society of Medical Oncology and the Spanish Society of Pathology. This expert group recommends determining in all cases of breast cancer the histologic grade and the alpha-estrogen receptor (ER), progesterone receptor, Ki-67 and HER2 status, in order to assist prognosis and establish therapeutic options, including hormone therapy, chemotherapy and anti-HER2 therapy. One of the four available genetic prognostic platforms (MammaPrint^®, Oncotype DX^®, Prosigna^® or EndoPredict^®) may be used in node-negative ER-positive patients to establish a prognostic category and decide with the patient whether adjuvant treatment may be limited to hormonal therapy. Newer technologies including next-generation sequencing, liquid biopsy, tumour-infiltrating lymphocytes or PD-1 determination are at this point investigational.

Personalized medicine in interstitial lung diseases

PURPOSE OF REVIEW

A number of recent studies have explored the possibility to apply personalized medicine to interstitial lung diseases (ILDs), particularly idiopathic pulmonary fibrosis (IPF), the most common and deadly of the idiopathic interstitial pneumonias. In our review, we summarize and discuss the most recent literature on personalized medicine in IPF as well as hypersensitivity pneumonitis and sarcoidosis, with emphasis on patient subgroups for which a personalized approach to disease prognostication and management may become a reality in the near future.

RECENT FINDINGS

Most of the studies that have explored the applicability of personalized medicine to ILDs have been conducted in patients with IPF. Such studies have suggested the existence of several distinct disease subgroups defined by similar genetic profiles, molecular pathways, exposures and individual lifestyles. Personalized medicine in hypersensitivity pneumonitis is in its infancy. The development and applicability of personalized medicine to sarcoidosis, on the other hand, remains problematic for several reasons, including the lack of a diagnostic gold standard, the highly variable and unpredictable disease course, particularly across patients of different ethnicities, the poor correlation between disease activity and disease severity and the lack of a validated management algorithm.

SUMMARY

A number of distinct patient subgroups have been identified in ILDs. Although available data need to be validated longitudinally, the possibility to study homogeneous groups of patients may allow prediction of disease behavior and response to treatment with dramatic clinical implications.

[Consensus statement on biomarkers in breast cancer by the Spanish Society of Pathology and the Spanish Society of Medical Oncology]

This consensus statement is a joint initiative of the Spanish Society of Pathology (SEAP) and the Spanish Society of Medical Oncology (SEOM). It revises and updates the recommendations for the use of biomarkers in the diagnosis and treatment of breast cancer. The group of experts recommends that, in all cases of breast cancer, the histologic grade and the alpha-estrogen receptor (ER), progesterone receptor, Ki-67 and HER2 status should be determined, in order to assist prognosis and establish therapeutic options, including hormone therapy, chemotherapy and anti-HER2 therapy. One of the four available genetic prognostic platforms (MammaPrint^®, Oncotype DX^®, Prosigna^® or EndoPredict^®) may be used in node-negative ER-positive patients to establish a prognostic category and decide, together with the patient, whether adjuvant treatment be limited to hormonal therapy. Newer technologies, including next generation sequencing, liquid biopsy, tumour infiltrating lymphocytes or PD-1 determination, are still investigational.

Targeted NGS, array-CGH, and patient-derived tumor xenografts for precision medicine in advanced breast cancer: a single-center prospective study

Background

Routine feasibility and clinical impact of genomics-based tumor profiling in advanced breast cancer (aBC) remains to be determined. We conducted a pilot study to evaluate whether precision medicine could be prospectively implemented for aBC patients in a single center and to examine whether patient-derived tumor xenografts (PDX) could be obtained in this population.

Results

Thirty-four aBC patients were included. Actionable targets were found in 28 patients (82%). A targeted therapy could be proposed to 22 patients (64%), either through a clinical trial (n=15) and/or using already registered drugs (n=21). Ten patients (29%) eventually received targeted treatment, 2 of them deriving clinical benefit. Of 22 patients subjected to mouse implantation, 10 had successful xenografting (45%), mostly in triple-negative aBC.

Methods

aBC patients accessible to tumor biopsy were prospectively enrolled at the Institut Paoli-Calmettes in the BC-BIO study (ClinicalTrials.gov, NCT01521676). Genomic profiling was established by whole-genome array comparative genomic hybridization (aCGH) and targeted next-generation sequencing (NGS) of 365 candidate cancer genes. For a subset of patients, a sample of fresh tumor was orthotopically implanted in humanized cleared fat pads of NSG mice for establishing PDX.

Conclusions

Precision medicine can be implemented in a single center in the context of clinical practice and may allow genomic-driven treatment in approximately 30% of aBC patients. PDX may be obtained in a significant fraction of cases.

Functional precision cancer medicine-moving beyond pure genomics

The essential job of precision medicine is to match the right drugs to the right patients. In cancer, precision medicine has been nearly synonymous with genomics. However, sobering recent studies have generally shown that most patients with cancer who receive genomic testing do not benefit from a genomic precision medicine strategy. Although some call the entire project of precision cancer medicine into question, I suggest instead that the tools employed must be broadened. Instead of relying exclusively on big data measurements of initial conditions, we should also acquire highly actionable functional information by perturbing-for example, with cancer therapies-viable primary tumor cells from patients with cancer.

How to emerge from the conservatism in clinical research methodology?

PURPOSE OF REVIEW

Despite recent changes in clinical research methodology, many challenges remain in drug development methodology.

RECENT FINDINGS

Advances in molecular biology and cancer treatments have changed the clinical research landscape. Thus, we moved from empirical clinical oncology to molecular and immunological therapeutic approaches. Along with this move, adapted dose-limiting toxicities definitions, endpoints, and dose escalation methods have been proposed. Moreover, the classical frontier between phase I, phase II, and phase III has become unclear in particular for immunological approaches. So, investigators are facing major challenges in drug development methodology.

SUMMARY

We propose to individualize clinical research using innovative approaches to significantly improve patient outcomes and targeting what is considered unmet need. Integrating high level of translational research and performing well designed biomarker studies with great potential for clinical practice are of utmost importance. This could be performed within new models of clinical research networks and by building a strong collaboration between academic, cooperative groups, on-site investigators, and pharma.

Synthetic lethality and cancer

A synthetic lethal interaction occurs between two genes when the perturbation of either gene alone is viable but the perturbation of both genes simultaneously results in the loss of viability. Key to exploiting synthetic lethality in cancer treatment are the identification and the mechanistic characterization of robust synthetic lethal genetic interactions. Advances in next-generation sequencing technologies are enabling the identification of hundreds of tumour-specific mutations and alterations in gene expression that could be targeted by a synthetic lethality approach. The translation of synthetic lethality to therapy will be assisted by the synthesis of genetic interaction data from model organisms, tumour genomes and human cell lines.