The Future of Interventions for Stage IV Colorectal Cancers

Future options for the management of stage IV colorectal cancer are primarily focused on personalized and directed therapies. Interventions include precision cancer medicine, utilizing nanocarrier platforms for directed chemotherapy, palliative pressurized intraperitoneal aerosol chemotherapy (PIPAC), adjunctive oncolytic virotherapy, and radioembolization techniques. Comprehensive genetic profiling provides specific tumor-directed therapy based on individual genetics. Biomimetic magnetic nanoparticles as chemotherapy delivery systems may reduce systemic side effects of traditional chemotherapy by targeting tumor cells and sparing healthy cells. PIPAC is a newly emerging option for patients with peritoneal metastasis from colorectal cancer and is now being used internationally, showing promising results as a palliative therapy for colorectal cancer. Oncolytic virotherapy is another emerging potential treatment option, especially when combined with standard chemotherapy and/or radiation, as well as immunotherapy. And finally, radioembolization with yttrium-90 ( 90 Y) microspheres has shown some success in treating patients with unresectable liver metastasis from colorectal cancer via selective arterial injection.

Clinical Significance of Multi-Cancer Genome Profiling: Data from a Single Hospital in Japan

BACKGROUND/AIM

Multi-cancer genome profiling (multi-CGP) testing intends to predict the therapeutic efficacy of anticancer medication treatments for eligible patients as part of "precision cancer care." The number of cases in which a new treatment was applied based on multi-CGP testing has been reported to be between 10% and 20% for all patients in Japan. This study aimed to determine the significance of multi-CGP testing in Japan by analyzing clinical data from multi-CGP testing in various solid cancers at our Hospital.

PATIENTS AND METHODS

A total of 230 patients examined by one of three tests for multi-CGP including NCC Oncopanel, FoundationOne CDx, and FoundationOne Liquid were retrospectively enrolled. Adequate treatment for each patient was discussed at the expert panel meeting according to the results from the genome profiling tests.

RESULTS

The most frequent cancer types enrolled in this study were pancreas cancer, bowel cancer, and biliary cancer. Of the 230 cases, 106 (46%) were druggable cases, and 21 (9.1%) were administered medication. Partial response (PR) effect was found in 7 (33.3%) of the 21 cases, of which 3 were biliary cancer and 3 had a BRCA2 mutation. Of all the 21 cases, 7 (33.3%) had the maximum treatment benefit of PR. Three cases of biliary tumors were found in the 7 PR cases within the 21 cases.

CONCLUSION

Of 230 patients, 21 were administered medication following multi-CGP testing data, especially frequent in biliary tumor patients. Multi-CGP testing might be particularly beneficial to patients with biliary tumors in Japan.

"How is it going to help?": Exploring Black breast cancer patients' questions about biomarker testing to predict chemotherapy-induced peripheral neuropathy

Objective

Many Black breast cancer patients experience chemotherapy-induced peripheral neuropathy (CIPN). Our study assessed Black breast cancer patients' questions about a biomarker test that can predict likelihood of CIPN.

Methods

Nineteen Black women who were previous/current breast cancer patients participated in focus groups. Researchers briefly explained CIPN and the biomarker test, and then participants were asked what questions they would have about the test and its use in treatment decisions. These participant-voiced questions composed the data for this study and were analyzed using thematic analysis.

Results

Participants' questions centered on six themes: reasons for the test, effect on timeline of breast cancer treatment, testing procedure, limits of test (including accuracy), research done to develop this test (including research participants), and concerns about personal information connected to the test (including DNA).

Conclusion

This study provides an exploratory look at questions that Black breast cancer patients may have about toxicity biomarker testing use in breast cancer treatment decisions.

Innovation

These findings provide a starting point for developing patient-centered approaches for integrating this precision medicine tool into clinical care. The methodological choice to generate participants' questions (rather than answers to a question) led to robust, actionable data.

Prognostic impact of cancer genomic profile testing for advanced or metastatic solid tumors in clinical practice

Cancer genomic profile (CGP) testing, which is covered by the national health insurance system in Japan, has been introduced as a routine clinical practice. However, the effects of CGP testing on prognoses remain unclear. Drug accessibility rates and prognoses after CGP testing were retrospectively investigated in 713 patients who underwent CGP testing examined by our molecular tumor board between November 2019 and October 2022,. Overall survival (OS) was examined using the log-rank test and the Kaplan-Meier method. The median age of patients (326 males and 387 females) was 58 years (12-85 years). CGP testing revealed one or more gene mutations in 681 cases (95.5%), among which actionable gene mutations were detected in 439 (61.6%). Although treatment options were recommended for 285 cases (40.0%) by the molecular tumor board, only 45 received treatment based on their gene mutations. During the median observation period of 8.6 months, 351 (49.2%) patients died of the exacerbation of existing diseases. No significant differences were observed in OS between patients treated with and without genomically matched therapy (p = 0.285). According to clinical responses to treatment based on gene mutations, median OS was significantly longer in patients who achieved partial response and stable disease (26.5 months; 95% CI 14.4-38.6) than in those with progressive disease and not evaluated (9.8 months; 95% CI 5.8-13.8, p = 0.013). Responses to treatment based on gene mutations may improve prognoses, and it is important to increase the drug accessibility rate after CGP testing.

Precision cancer medicine: Concepts, current practice, and future developments

Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.

Targeting the FGF/FGFR axis and its co-alteration allies

BACKGROUND

We analyzed the FGF/FGFR and co-alteration cancer landscape, hypothesizing that combination therapy might be useful in the presence of co-drivers.

MATERIALS AND METHODS

We describe FGF/FGFR-altered pathways, prognosis, and co-alterations [cBioPortal (N = 7574)] and therapeutic outcomes [University of California San Diego Molecular Tumor Board (MTB) (N = 16)].

RESULTS

Patients whose cancers harbored FGF/FGFR alterations (N = 1074) versus those without them (N = 6500) had shorter overall survival (OS) (median: 23.1 versus 26.4 months, P = 0.038) (cBioPortal). Only 6.1% (65/1074 patients) had no pathogenic co-alterations accompanying FGF/FGFR axis abnormalities. The most frequently co-altered pathways/genes involved: TP53 (70%); cell cycle (58%); PI3K (55%); and receptor tyrosine kinases and mitogen-activated protein kinase (MAPK) (65%). Harboring alterations in both FGF/FGFR and in the TP53 pathway or in the cell cycle pathway correlated with shorter OS (versus FGF/FGFR-altered without those co-altered signals) (P = 0.0001 and 0.0065). Four of 16 fibroblast growth factor receptor (FGFR) inhibitor-treated patients presented at MTB attained durable partial responses (PRs) (9, 12, 22+, and 52+ months); an additional two, stable disease (SD) of ≥6 months (13+ and 15 months) [clinical benefit rate (SD ≥ 6 months/PR) = 38%]. Importantly, six patients with cyclin pathway co-alterations received the CDK4/6 inhibitor palbociclib (75 mg p.o. 3 weeks on, 1 week off) and the multikinase FGFR inhibitor lenvatinib (10 mg p.o. daily); three (50%) achieved a PR [9 (ovarian), 12 (biliary), and 52+ months (osteosarcoma)]. Palbociclib and lenvatinib were tolerated well.

CONCLUSIONS

FGF/FGFR alterations portend a poor prognosis and are frequently accompanied by pathogenic co-aberrations. Malignancies harboring co-alterations that activate both cyclin and FGFR pathways can be co-targeted by CDK4/6 and FGFR inhibitors.

Cost-effectiveness of molecularly matched off-label therapies for end-stage cancer - the MetAction precision medicine study

BACKGROUND

Precision cancer medicine (PCM), frequently used for the expensive and often modestly efficacious off-label treatment with medications matched to the tumour genome of end-stage cancer, challenges healthcare resources. We compared the health effects, costs and cost-effectiveness of our MetAction PCM study with corresponding data from comparator populations given best supportive care (BSC) in two external randomised controlled trials.

METHODS

We designed three partitioned survival models to evaluate the healthcare costs and quality-adjusted life years (QALYs) as the main outcomes. Cost-effectiveness was calculated as the incremental cost-effectiveness ratio (ICER) of PCM relative to BSC with an annual willingness-to-pay (WTP) threshold of EUR 56,384 (NOK 605,000). One-way and probabilistic sensitivity analyses addressed uncertainty.

RESULTS

We estimated total healthcare costs (relating to next-generation sequencing (NGS) equipment and personnel wages, molecularly matched medications to the patients with an actionable tumour target and follow-up of the responding patients) and the health outcomes for the MetAction patients versus costs (relating to estimated hospital admission) and outcomes for the BSC cases. The ICERs for incremental QALYs were twice or more as high as the WTP threshold and relatively insensitive to cost decrease of the NGS procedures, while reduction of medication prices would contribute significantly towards a cost-effective PCM strategy.

CONCLUSIONS

The models suggested that the high ICERs of PCM were driven by costs of the NGS diagnostics and molecularly matched medications, with a likelihood for the strategy to be cost-effective defying WTP constraints. Reducing drug expenses to half the list price would likely result in an ICER at the WTP threshold. This can be an incentive for a public-private partnership for sharing drug costs in PCM, exemplified by ongoing European initiatives.

CLINICALTRIALS.GOV, IDENTIFIER

NCT02142036.

Self-Assembly of Intelligent Nanoplatform for Endogenous H2S-Triggered Multimodal Cascade Therapy of Colon Cancer

The specific in situ generation and activation of therapeutic agents with high spatiotemporal precision is expected to revolutionize cancer treatment. Here, we develop an intelligent nanoplatform (termed as NP-Cu), which is constructed by assembling photosensitizer chlorin e6 (Ce6), hypoxia-responsive prodrug banoxantrone (AQ4N) with clickable dibenzocyclooctyne (DIBO) functionalized lysine (D-K), and cyclen-Cu²⁺ complex, for improving combination anticancer therapy. Cyclen-Cu²⁺ complex-induced photodynamic therapy (PDT) quenching in NP-Cu can be effectively and selectively activated by tumor-overproduced hydrogen sulfide (H₂S). More importantly, the reaction of endogenous H₂S with Cu²⁺ can generate photothermal agent copper sulfide (CuS) for photothermal therapy (PTT). Furthermore, with the activation of PTT and PDT, intracellular hypoxic stress is amplified to trigger AQ4N-associated chemodynamic therapy (CDT), leading to light-enhanced cascade therapy of PDT, PTT and CDT. Therefore, we present a simple and practical strategy for developing pathological stimuli responsive combination therapy, which has the potential of advancing precision cancer medicine.

Cost-effectiveness of precision cancer medicine-current challenges in the use of next generation sequencing for comprehensive tumour genomic profiling and the role of clinical utility frameworks (Review)

Precision cancer medicine (PCM) is an emerging paradigm in oncology, which includes tumour comprehensive genomic profiling (CGP) to enable molecularly guided therapy. However, cost-effectiveness analyses of PCM are faced with several challenges and, thus, its cost-effectiveness remains unclear. Early trials using only molecularly guided therapy were faced with the challenge of providing adequate measures of outcome, which probably explains the modest treatment benefits demonstrated. Endpoints like the progression-free survival (PFS)2/PFS1 ratio may assist in overcoming this issue. Moreover, specific tumour subtypes appear to benefit more from PCM. Costs associated with next-generation sequencing (NGS) for CGP are decreasing, but targeted therapy itself represents a major cost driver. CGP not only enables prediction of response to treatment, but also resistance, and could thus prevent administration of unnecessary (and costly) therapies. In clinical practice, the presence of clinical frameworks, such as the Recommendations for the Use of NGS for Patients with Metastatic Cancers from the ESMO Precision Medicine Working Group, and the ESMO Scale for Clinical Actionability of Molecular Targets, are essential in appropriately identifying situations where PCM is clinically meaningful, thereby improving its cost-effectiveness.

Ovarian Cancer With Breast Metastasis and Two Pathogenic Variants of BRCA1 Gene

Ovarian cancer is the second most common gynecologic cancer after uterine cancer in the United States. Ovarian cancer ranks sixth in cancer deaths among women, accounting for more deaths than other female reproductive system cancers. Breast metastasis in ovarian cancer is a rare presentation and predicts a poor prognosis and challenging management. Our case is a 42-year-old Chinese woman with high-grade serous ovarian carcinoma that presents with metastasis to the breast during the course of her illness. Genetic evaluation of the ovarian tumor showed two BRCA1 pathogenic variants. Germline pathogenic variant of c.2110_2111DelAA and a somatic variant of c.4071_4096+14del40. Our patient was offered different treatment regimens but showed progression of her disease. The low survival rate and high recurrence rate in ovarian cancer show that we still need to investigate our current approved treatments. Our report aims to shed light on the genetic evaluation of ovarian tumors and treatment options available in refractory cases of progressive ovarian cancer. Furthermore, we explain our investigational therapy regimen and the reasoning behind it.

Precision Medicine: An Emerging Paradigm for Improved Diagnosis and Safe Therapy in Pediatric Oncology

Cancer is a lethal disease that kills a great number of people each year. Standard treatments such as chemotherapy or radiation are only effective in a small percentage of individuals due to illness variability. Tumors can be caused by a variety of genetic factors and express a variety of proteins depending on the individual. Because of developments in high-throughput technology, there has been a flood of large-scale biological data produced in recent decades. As a result, the focus of medical research has evolved. It was a once-in-a-lifetime chance for translational research to explore molecular alterations across the entire genome. In this setting, precision medicine was developed, and the possibility of better diagnostic and treatment tools became a reality. This is especially true in the case of cancer, which is becoming more prevalent around the world. The goal of this study is to look at precision medicine technology and its applications to cancer, with a focus on children. The inherent diversity of cancer lends itself to the rapidly expanding field of precision and personalized medicine.

Cancer Predisposition Sequencing Reporter (CPSR): A flexible variant report engine for high-throughput germline screening in cancer

The value of high-throughput germline genetic testing is increasingly recognized in clinical cancer care. Disease-associated germline variants in cancer patients are important for risk management and surveillance, surgical decisions and can also have major implications for treatment strategies since many are in DNA repair genes. With the increasing availability of high-throughput DNA sequencing in cancer clinics and research, there is thus a need to provide clinically oriented sequencing reports for germline variants and their potential therapeutic relevance on a per-patient basis. To meet this need, we have developed the Cancer Predisposition Sequencing Reporter (CPSR), an open-source computational workflow that generates a structured report of germline variants identified in known cancer predisposition genes, highlighting markers of therapeutic, prognostic and diagnostic relevance. A fully automated variant classification procedure based on more than 30 refined American College of Medical Genetics and Genomics (ACMG) criteria represents an integral part of the workflow. Importantly, the set of cancer predisposition genes profiled in the report can be flexibly chosen from more than 40 virtual gene panels established by scientific experts, enabling customization of the report for different screening purposes and clinical contexts. The report can be configured to also list actionable secondary variant findings, as recommended by ACMG. CPSR demonstrates comparable sensitivity and specificity for the detection of pathogenic variants when compared to other algorithms in the field. Technically, the tool is implemented in Python/R, and is freely available through Docker technology. Source code, documentation, example reports and installation instructions are accessible via the project GitHub page: https://github.com/sigven/cpsr.

Construction of Tissue-Level Cancer-Vascular Model with High-Precision Position Control via In Situ 3D Cell Printing

During tumor progression, the size and location of the tumor are important factors closely associated with the metastatic potential of the cancer as they largely govern tumor hypoxia and angiogenesis. However, despite the achievements of previous studies, these critical factors are poorly studied, mainly due to the lack of a flexible technique that can readily control 3D tumor mimicking constructs and their spatial relations with vasculature. Here, a novel tissue-level platform consisting of a metastatic cancer unit (MCU) and a perfusable vascular endothelium system (VES) is presented using in situ 3D cell printing. Size-tunable and position-controllable 3D cancer spheroids (500-1000 µm) are directly printed within the established bath bioink with a self-driven perfusable vascular channel. The cancer-vascular interactions are generated through controlling the distance between MCU and VES to investigate metastasis-associated changes at adjacent and distal regions. The result shows that MCU in 600 µm diameter includes hypoxia, invasion, and angiogenetic signaling. The further observations demonstrate that the proximity of MCU to VES augments the epithelial-mesenchymal transition (EMT) in MCU and vascular dysfunction/inflammation in VES, corroborating the positional significance in tumor metastasis. The platform with the precise-positioning control enables the recapitulation of patient's detailed metastatic progression, opening the chance for precision cancer medicine.

Prediction of Sensitivity and Efficacy of Clinical Chemotherapy Using Larval Zebrafish Patient-Derived Xenografts of Gastric Cancer

Background

Perioperative chemotherapy has been accepted as one of the most common approaches for locally advanced gastric cancer. However, the efficacy of chemotherapy varies among patients, and there is no effective method to predict the chemotherapy efficacy currently. We previously established the first larval zebrafish patient-derived xenografts (zPDXs) of gastric cancer as a platform for the translational research and personalized treatment. The objective of this study was to investigate the feasibility of screening individualized chemotherapeutics using the zPDXs.

Methods

We further optimized this zPDXs platform including administration route, drug dosing, and rhythm to develop a stable and reliable protocol for chemotherapeutics screening. Using the novel platform, we investigated the chemosensitivity of 5-fluorouracil, cisplatin, docetaxel, and doxorubicin for gastric cancer patients.

Results

We showed that the engrafted zebrafish retained the original prominent cell components of the corresponding human tumor tissues, and we successfully obtained the results of chemosensitivity of 5-fluorouracil, cisplatin, docetaxel, and doxorubicin for 28 patients with locally advanced gastric cancer. These patients underwent radical gastrectomy for curative intent and 27 cases received postoperative adjuvant chemotherapy. We revealed that the chemosensitivity obtained from zPDXs was consistent with the clinical responses in these patients (P = 0.029). More importantly, the responder drug(s) from zPDXs used or not was the only risk factor for early-stage recurrence in these 27 patients (P = 0.003).

Conclusion

Our study with the largest sample size so far suggests that larval zPDXs help to predict the chemotherapeutics response and to achieve precise chemotherapy for gastric cancer.

Molecular Features of Cancers Exhibiting Exceptional Responses to Treatment

A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories-DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis-with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy.

Reduced Mitochondrial Apoptotic Priming Drives Resistance to BH3 Mimetics in Acute Myeloid Leukemia

Acquired resistance to BH3 mimetic antagonists of BCL-2 and MCL-1 is an important clinical problem. Using acute myelogenous leukemia (AML) patient-derived xenograft (PDX) models of acquired resistance to BCL-2 (venetoclax) and MCL-1 (S63845) antagonists, we identify common principles of resistance and persistent vulnerabilities to overcome resistance. BH3 mimetic resistance is characterized by decreased mitochondrial apoptotic priming as measured by BH3 profiling, both in PDX models and human clinical samples, due to alterations in BCL-2 family proteins that vary among cases, but not to acquired mutations in leukemia genes. BCL-2 inhibition drives sequestered pro-apoptotic proteins to MCL-1 and vice versa, explaining why in vivo combinations of BCL-2 and MCL-1 antagonists are more effective when concurrent rather than sequential. Finally, drug-induced mitochondrial priming measured by dynamic BH3 profiling (DBP) identifies drugs that are persistently active in BH3 mimetic-resistant myeloblasts, including FLT-3 inhibitors and SMAC mimetics.

Comprehensive genomic profiling for patients with chemotherapy-naïve advanced cancer

Comprehensive genomic profiling (CGP) testing by next‐generation sequencing has been introduced into clinical practice as part of precision cancer medicine to select effective targeted therapies. However, whether CGP testing at the time of first‐line chemotherapy could be clinically useful is not clear. We conducted this single‐center, prospective, observational study to investigate the feasibility of CGP testing for chemotherapy‐naïve patients with stage III/IV gastrointestinal cancer, rare cancer, and cancer of unknown primary, using the FoundationOne^® companion diagnostic (F1CDx) assay. The primary outcome was the detection rate of at least one actionable/druggable cancer genomic alteration. Actionable/druggable cancer genomic alterations were determined by the F1CDx report. An institutional molecular tumor board determined the molecular‐based recommended therapies. A total of 197 patients were enrolled from October 2018 to June 2019. CGP success rate was 76.6% (151 of 197 patients), and median turnaround time was 19 days (range: 10‐329 days). Actionable and druggable cancer genomic alterations were reported in 145 (73.6%) and 124 (62.9%) patients, respectively. The highest detection rate of druggable genomic alterations in gastrointestinal cancers was 80% in colorectal cancer (48 of 60 patients). Molecular‐based recommended therapies were determined in 46 patients (23.4%). CGP testing would be a useful tool for the identification of a potentially effective first‐line chemotherapy.

Computational Cancer Cell Models to Guide Precision Breast Cancer Medicine

Background: Large-scale screening of drug sensitivity on cancer cell models can mimic in vivo cellular behavior providing wider scope for biological research on cancer. Since the therapeutic effect of a single drug or drug combination depends on the individual patient’s genome characteristics and cancer cells integration reaction, the identification of an effective agent in an in vitro model by using large number of cancer cell models is a promising approach for the development of targeted treatments. Precision cancer medicine is to select the most appropriate treatment or treatments for an individual patient. However, it still lacks the tools to bridge the gap between conventional in vitro cancer cell models and clinical patient response to inhibitors. Methods: An optimal two-layer decision system model is developed to identify the cancer cells that most closely resemble an individual tumor for optimum therapeutic interventions in precision cancer medicine. Accordingly, an optimal grid parameters selection is designed to seek the highest accordance for treatment selection to the patient’s preference for drug response and in vitro cancer cell drug screening. The optimal two-layer decision system model overcomes the challenge of heterology data comparison between the tumor and the cancer cells, as well as between the continual variation of drug responses in vitro and the discrete ones in clinical practice. We simulated the model accuracy using 681 cancer cells’ mRNA and associated 481 drug screenings and validated our results on 315 breast cancer patients drug selection across seven drugs (docetaxel, doxorubicin, fluorouracil, paclitaxel, tamoxifen, cyclophosphamide, lapitinib). Results: Comparing with the real response of a drug in clinical patients, the novel model obtained an overall average accordance over 90.8% across the seven drugs. At the same time, the optimal cancer cells and the associated optimal therapeutic efficacy of cancer drugs are recommended. The novel optimal two-layer decision system model was used on 1097 patients with breast cancer in guiding precision medicine for a recommendation of their optimal cancer cells (30 cancer cells) and associated efficacy of certain cancer drugs. Our model can detect the most similar cancer cells for each individual patient. Conclusion: A successful clinical translation model (optimal two-layer decision system model) was developed to bridge in-vitro basic science to clinical practice in a therapeutic intervention application for the first time. The novel tool kills two birds with one stone. It can help basic science to seek optimal cancer cell models for an individual tumor, while prioritizing clinical drugs’ recommendations in practice. Tool associated platform website: We extended the breast cancer research to 32 more types of cancers across 45 therapy predictions.

Chasing the FOXO3: Insights into Its New Mitochondrial Lair in Colorectal Cancer Landscape

Colorectal cancer (CRC) poses a formidable challenge in terms of molecular heterogeneity, as it involves a variety of cancer-related pathways and molecular changes unique to an individual’s tumor. On the other hand, recent advances in DNA sequencing technologies provide an unprecedented capacity to comprehensively identify the genetic alterations resulting in tumorigenesis, raising the hope that new therapeutic approaches based on molecularly targeted drugs may prevent the occurrence of chemoresistance. Regulation of the transcription factor FOXO3a in response to extracellular cues plays a fundamental role in cellular homeostasis, being part of the molecular machinery that drives cells towards survival or death. Indeed, FOXO3a is controlled by a range of external stimuli, which not only influence its transcriptional activity, but also affect its subcellular localization. These regulation mechanisms are mediated by cancer-related signaling pathways that eventually drive changes in FOXO3a post-translational modifications (e.g., phosphorylation). Recent results showed that FOXO3a is imported into the mitochondria in tumor cells and tissues subjected to metabolic stress and cancer therapeutics, where it induces expression of the mitochondrial genome to support mitochondrial metabolism and cell survival. The current review discusses the potential clinical relevance of multidrug therapies that drive cancer cell fate by regulating critical pathways converging on FOXO3a.

Next generation sequencing-based gene panel tests for the management of solid tumors

Next generation sequencing (NGS) has been an invaluable tool to put genomic sequencing into clinical practice. The incorporation of clinically relevant target sequences into NGS-based gene panel tests has generated practical diagnostic tools that enable individualized cancer-patient care. The clinical utility of gene panel testing includes investigation of the genetic basis for an individual's response to therapy, such as signaling pathways associated with a response to specific therapies, microsatellite instability and a hypermutated phenotype, and deficiency in the DNA double-strand break repair pathway. In this review, we describe the concept of precision cancer medicine using target sequences in gene panel tests as well as the importance of the control of sample quality in routine NGS-based genomic testing. We describe geographic and ethnic differences in cancer genomes, and discuss issues that need to be addressed in the future based on our experiences in Japan.

The Emerging Potential for Network Analysis to Inform Precision Cancer Medicine

Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that targets BCR-ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However, biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but also by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis, and the path for such tools to the clinic.

Precision cancer therapy: profiting from tumor specific defects in the DNA damage tolerance system

DNA damage tolerance (DDT) enables replication to continue in the presence of a damaged template and constitutes a key step in DNA interstrand crosslink repair. In this way DDT minimizes replication stress inflicted by a wide range of endogenous and exogenous agents, and provides a critical first line defense against alkylating and platinating chemotherapeutics. Effective DDT strongly depends on damage-induced, site-specific PCNA-ubiquitination at Lysine (K) 164 by the E2/E3 complex (RAD6/18). A survey of The Cancer Genome Atlas (TCGA) revealed a high frequency of tumors presents RAD6/RAD18 bi-allelic inactivating deletions. For instance, 11% of renal cell carcinoma and 5% of pancreatic tumors have inactivating RAD18-deletions and 7% of malignant peripheral nerve sheath tumors lack RAD6B. To determine the potential benefit for tumor-specific DDT defects, we followed a genetic approach by establishing unique sets of DDT-proficient Pcna^K164 and -defective Pcna^K164R lymphoma and breast cancer cell lines. In the absence of exogenous DNA damage, Pcna^K164R tumors grew comparably to their Pcna^K164 controls in vitro and in vivo. However, DDT-defective lymphomas and breast cancers were compared to their DDT-proficient controls hypersensitive to the chemotherapeutic drug cisplatin (CsPt), both in vitro and in vivo. CsPt strongly inhibited tumor growth and the overall survival of tumor bearing mice greatly improved in the DDT-defective condition. These insights open new therapeutic possibilities for precision cancer medicine with DNA damaging chemotherapeutics and optimize Next-Generation-Sequencing (NGS)-based cancer-diagnostics, -therapeutics, and -prognosis.

The status of transarterial chemoembolization treatment in the era of precision oncology

Transarterial chemoembolization (TACE) is the gold standard of therapy for patients with unresectable intermediate stage hepatocellular carcinoma (HCC), and is also commonly used as postresection adjuvant therapy in Asia. The delivery of TACE is highly variable from center to center, and clinical decision making for patients is based primarily on tumor staging guidelines, with very little focus on individualized tumor features. This review will discuss recent efforts for improving patient outcomes with TACE treatment through personalized medicine advances, including ongoing clinical trials investigating the combination of targeted therapy with TACE and the discovery of prognostic biomarkers for predicting TACE response.

Clinical sequencing using a next-generation sequencing-based multiplex gene assay in patients with advanced solid tumors

Advances in next‐generation sequencing (NGS) technologies have enabled physicians to test for genomic alterations in multiple cancer‐related genes at once in daily clinical practice. In April 2015, we introduced clinical sequencing using an NGS‐based multiplex gene assay (OncoPrime) certified by the Clinical Laboratory Improvement Amendment. This assay covers the entire coding regions of 215 genes and the rearrangement of 17 frequently rearranged genes with clinical relevance in human cancers. The principal indications for the assay were cancers of unknown primary site, rare tumors, and any solid tumors that were refractory to standard chemotherapy. A total of 85 patients underwent testing with multiplex gene assay between April 2015 and July 2016. The most common solid tumor types tested were pancreatic (n = 19; 22.4%), followed by biliary tract (n = 14; 16.5%), and tumors of unknown primary site (n = 13; 15.3%). Samples from 80 patients (94.1%) were successfully sequenced. The median turnaround time was 40 days (range, 18–70 days). Potentially actionable mutations were identified in 69 of 80 patients (86.3%) and were most commonly found in TP53 (46.3%), KRAS (23.8%), APC (18.8%), STK11 (7.5%), and ATR (7.5%). Nine patients (13.0%) received a subsequent therapy based on the NGS assay results. Implementation of clinical sequencing using an NGS‐based multiplex gene assay was feasible in the clinical setting and identified potentially actionable mutations in more than 80% of patients. Current challenges are to incorporate this genomic information into better therapeutic decision making.

Extracting tumor tissue immune status from expression profiles: correlating renal cancer prognosis with tumor-associated immunome

Investigating the expression of genes in cancer-associated immune cells (immunome) is imperative for prognosis prediction. However, evaluating the expression of immune-associated genes within cancer biopsy is subject to significant inconsistencies related to the sampling methodology. Here, we present immFocus, a method for extracting immune signals from total RNA sequencing of tumor biopsies, intended for immunity depiction and prognosis evaluation. It is based on reducing the variation which biopsy preparation adds to the apparent expression levels of immune genes. We employed immFocus to normalize gene expression with an immune index using data obtained from renal clear cell carcinoma biopsies. Genes that became less variable due to normalization were found to be preferentially immune-related. Moreover, immune-related genes tended to become more prognostic due to the normalization. These results demonstrate, for the first time, that whole transcriptome sequencing can be used for interrogation of a cancer immunome and for advancing immune-based prognosis.

A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes

OBJECTIVE

Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics.

METHODS

We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network.

RESULTS

We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1).

CONCLUSIONS

In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics.

Cancer Evolution and the Limits of Predictability in Precision Cancer Medicine

The ability to predict the future behavior of an individual cancer is crucial for precision cancer medicine. The discovery of extensive intratumor heterogeneity and ongoing clonal adaptation in human tumors substantiated the notion of cancer as an evolutionary process. Random events are inherent in evolution and tumor spatial structures hinder the efficacy of selection, which is the only deterministic evolutionary force. This review outlines how the interaction of these stochastic and deterministic processes, which have been extensively studied in evolutionary biology, limits cancer predictability and develops evolutionary strategies to improve predictions. Understanding and advancing the cancer predictability horizon is crucial to improve precision medicine outcomes.

Advances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomes

Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of >10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine.