Comprehensive sampling of the lung microbiome in early-stage non-small cell lung cancer.

Objectives: Data are scarce on whether the composition of the lung microbiome (extending from the nasopharynx to the peripheral lung tissue) varies according to histology or grade of non-small cell lung cancer. We hypothesized that the composition of the lung microbiome would vary according to the histology and the grade of non-small cell lung cancer. Methods: We collected naso-oral and central lobar (cancer affected, ipsilateral unaffected, and contralateral unaffected) bronchoalveolar lavage fluid and brushing samples from patients with clinical early-stage lung cancer between July 2018 and February 2020 at a single academic center. We performed bacterial 16S rRNA sequencing and then compared clinical and pathologic findings with microbiome signatures. Results: Samples were collected from 28 patients. Microbial composition in affected lobes displayed unique enrichment of oropharyngeal bacterial species that was significantly different compared with that from the unaffected contralateral lobes; patients with chronic obstructive pulmonary disease had similar diversity to those without chronic obstructive pulmonary disease (P = .1312). The lung microbiome diversity in patients with adenocarcinoma was similar to those with squamous cell cancer (P = .27). There were no differences in diversity or composition in the unaffected lobes of patients with adenocarcinoma versus squamous cell cancer. There was a trend toward lower lung microbial diversity in poorly differentiated adenocarcinomas compared with well-differentiated adenocarcinomas (P = .08). Conclusions: The lung microbiota differs between cancer affected and unaffected lobes in the same patient. Furthermore, poorly differentiated lung cancers were associated with lower microbial diversity. Larger studies will be required to confirm these findings.

Systemic Therapy for Small-Cell Lung Cancer: ASCO-Ontario Health (Cancer Care Ontario) Guideline.

PURPOSE: To provide evidence-based recommendations to practicing clinicians on the management of patients with small-cell lung cancer. METHODS: An Expert Panel of medical oncology, thoracic surgery, radiation oncology, pulmonary, community oncology, research methodology, and advocacy experts were convened to conduct a literature search, which included systematic reviews, meta-analyses, and randomized controlled trials published from 1990 through 2022. Outcomes of interest included response rates, overall survival, disease-free survival or recurrence-free survival, and quality of life. Expert Panel members used available evidence and informal consensus to develop evidence-based guideline recommendations. RESULTS: The literature search identified 95 relevant studies to inform the evidence base for this guideline. RECOMMENDATIONS: Evidence-based recommendations were developed to address systemic therapy options, timing of therapy, treatment in patients who are older or with poor performance status, role of biomarkers, and use of myeloid-supporting agents in patients with small-cell lung cancer.Additional information is available at www.asco.org/thoracic-cancer-guidelines.

The Lung Microbiome in Carcinogenesis and Immunotherapy Treatment.

ABSTRACT: Lung cancer is the leading cause of cancer-related deaths. Over the past 10 years, significant advances in treatment modalities, including immune checkpoint inhibitor (ICI) blockade, have led to improved outcomes. Elucidating predicative biomarkers in responders and nonresponders to ICI will lead to development of therapeutic targets that could enhance ICI efficacy. Recently, the gut microbiome was identified as a predictive biomarker for ICI in patients with multiple cancer types. However, it is unclear how other host microbiomes influence tumorigenesis and response to ICI. Other groups have explored the lung microbiome as it relates to carcinogenesis and immunotherapy efficacy. In this review, we explore the role of the lung microbiome in health and disease. We also review the current state of lung microbiome research as it relates to tumorigenesis and treatments and provide potential insights into how the lung microbiome could improve outcomes in patients with cancer.

The Prognostic and Therapeutic Potential of DNA Damage Repair Pathway Alterations and Homologous Recombination Deficiency in Lung Cancer.

Lung cancer remains the second most commonly diagnosed cancer worldwide and the leading cause of cancer-related mortality. The mapping of genomic alterations and their role in lung-cancer progression has been followed by the development of new therapeutic options. Several novel drugs, such as targeted therapy and immunotherapy, have significantly improved outcomes. However, many patients with lung cancer do not benefit from existing therapies or develop progressive disease, leading to increased morbidity and mortality despite initial responses to treatment. Alterations in DNA-damage repair (DDR) genes represent a cancer hallmark that impairs a cell's ability to prevent deleterious mutation accumulation and repair. These alterations have recently emerged as a therapeutic target in breast, ovarian, prostate, and pancreatic cancers. The role of DDR alterations remains largely unknown in lung cancer. Nevertheless, recent research efforts have highlighted a potential role of some DDR alterations as predictive biomarkers of response to treatment. Despite the failure of PARP inhibitors (main class of DDR targeting agents) to improve outcomes in lung cancer patients, there is some evidence suggesting a role of PARP inhibitors and other DDR targeting agents in benefiting a distinct subset of lung cancer patients. In this review, we will discuss the existing literature on DDR alterations and homologous recombination deficiency (HRD) state as predictive biomarkers and therapeutic targets in both non-small cell lung and small cell lung cancer.

Metabolic collateral lethal target identification reveals MTHFD2 paralogue dependency in ovarian cancer.

Recurrent loss-of-function deletions cause frequent inactivation of tumour suppressor genes but often also involve the collateral deletion of essential genes in chromosomal proximity, engendering dependence on paralogues that maintain similar function. Although these paralogues are attractive anticancer targets, no methodology exists to uncover such collateral lethal genes. Here we report a framework for collateral lethal gene identification via metabolic fluxes, CLIM, and use it to reveal MTHFD2 as a collateral lethal gene in UQCR11-deleted ovarian tumours. We show that MTHFD2 has a non-canonical oxidative function to provide mitochondrial NAD+, and demonstrate the regulation of systemic metabolic activity by the paralogue metabolic pathway maintaining metabolic flux compensation. This UQCR11-MTHFD2 collateral lethality is confirmed in vivo, with MTHFD2 inhibition leading to complete remission of UQCR11-deleted ovarian tumours. Using CLIM's machine learning and genome-scale metabolic flux analysis, we elucidate the broad efficacy of targeting MTHFD2 despite distinct cancer genetic profiles co-occurring with UQCR11 deletion and irrespective of stromal compositions of tumours.

Characterization of pneumonia and other factors leading to poorer survival across all age groups in patients with non-small cell lung cancer (NSCLC).

BACKGROUND: Lung cancer death rates and incidence in both men and women have decreased over the past two decades. However, certain subsets of non-small cell lung cancer (NSCLC) have arisen with poor outcomes. Identifying factors which contribute to poorer outcomes as well as those that inform early detection strategies remain unmet needs. We present data from a contemporaneous group of NSCLC patients that received care at a single University teaching hospital to understand clinical and pathological factors influencing outcomes in the past decade. METHODS: A cohort of 2,289 patients with NSCLC who established care at the Rogel Cancer Center, University of Michigan between January 2011 and April 2019 were identified. Patient characteristics and clinical outcomes were recorded using electronic health records. The Kaplan-Meier method and the Cox proportional model were used to assess relationship between clinic-pathological factors and survival. RESULTS: Of the 2,289 patients, 92% were >50 years of age while 8% were <50 years of age. The majority (70%) of older patients were former smokers. The majority (61%) of younger patients were diagnosed as having Stage IV NSCLC. Among younger patients, 87% had histologically confirmed non-squamous histology. Univariate analysis revealed that overall survival was significantly lower in patients diagnosed with pneumonia prior to the diagnosis of NSCLC than in those who were not diagnosed with pneumonia (1.9 vs. 21.8 months; P<0.001). Multivariate analysis revealed that older patients had poorer survival than younger patients (HR 1.57, 95% CI: 1.10-2.06, P=0.01) and that patients diagnosed with pneumonia prior to their lung cancer diagnosis had poorer survival across all age groups, particularly in those with advanced-stage disease. CONCLUSIONS: Findings from this study merit prospective studies to understand cost-benefit ratio of follow- up cross sectional imaging of all patients diagnosed with unprovoked pneumonia, including in younger non/current smokers.

The Lung Microbiome: A Central Mediator of Host Inflammation and Metabolism in Lung Cancer Patients?

Lung cancer is the leading cause of cancer-related death. Over the past 5-10 years lung cancer outcomes have significantly improved in part due to better treatment options including immunotherapy and molecularly targeted agents. Unfortunately, the majority of lung cancer patients do not enjoy durable responses to these new treatments. Seminal research demonstrated the importance of the gut microbiome in dictating responses to immunotherapy in melanoma patients. However, little is known regarding how other sites of microbiota in the human body affect tumorigenesis and treatment responses. The lungs were traditionally thought to be a sterile environment; however, recent research demonstrated that the lung contains its own dynamic microbiota that can influence disease and pathophysiology. Few studies have explored the role of the lung microbiome in lung cancer biology. In this review article, we discuss the links between the lung microbiota and cancer, with particular focus on immune responses, metabolism and strategies to target the lung microbiome for cancer prevention.

Cyclin-dependent kinase inhibitors for the treatment of lung cancer.

INTRODUCTION: Cyclin-dependent kinases (CDKs) are critical regulators of cell cycle progression in both normal and malignant cells, functioning through complex molecular interactions. Deregulation of CDK-dependent pathways is commonly found in both non-small cell and small cell lung cancer, and these derangements suggest vulnerabilities that can be exploited for clinical benefit. AREAS COVERED: In this review, the authors present an overview of the biology of CDKs in normal and malignant cells, with a focus on lung cancer, followed by an assessment of preclinical work that has demonstrated the vital role of CDKs in lung cancer development and progression, and the activity of CDK inhibitors in a variety of lung cancer models. Finally, the experience with clinical trials of CDK inhibitors in lung cancer is discussed along with the current status of these agents in cancer therapy. EXPERT OPINION: Despite strong biological rationale and promising preclinical studies, the results of clinical trials of CDK inhibitors in lung cancer have thus far been disappointing. Further clinical development of CDK inhibitors in lung cancer will depend on the identification of predictive biomarkers and the design of combination regimens that take advantage of the unique molecular alterations that drive lung cancer growth and survival.

Synthetic lethality: a step forward for personalized medicine in cancer.

Synthetic lethality occurs between two genes when silencing of either gene alone enables viable outcomes but inhibition of both is lethal. Understanding context-dependent functioning of synthetic lethality allows therapeutic targeting in cancer. Furthermore, the paradigm shift toward precision medicine to treat cancer necessitates the establishment of biomarkers to help determine which patient populations might respond to specific drug combinations. Elucidating synthetically lethal gene combinations in cancer could establish clinically relevant drug combinations as well as biomarkers to better treat patients. Here, we have reviewed the recent synthetically lethal gene combinations in preclinical and clinical settings and discuss how this approach could help reveal potential biomarkers.

Generation of Human Fatty Livers Using Custom-Engineered Induced Pluripotent Stem Cells with Modifiable SIRT1 Metabolism.

The mechanisms by which steatosis of the liver progresses to non-alcoholic steatohepatitis and end-stage liver disease remain elusive. Metabolic derangements in hepatocytes controlled by SIRT1 play a role in the development of fatty liver in inbred animals. The ability to perform similar studies using human tissue has been limited by the genetic variability in man. We generated human induced pluripotent stem cells (iPSCs) with controllable expression of SIRT1. By differentiating edited iPSCs into hepatocytes and knocking down SIRT1, we found increased fatty acid biosynthesis that exacerbates fat accumulation. To model human fatty livers, we repopulated decellularized rat livers with human mesenchymal cells, fibroblasts, macrophages, and human SIRT1 knockdown iPSC-derived hepatocytes and found that the human iPSC-derived liver tissue developed macrosteatosis, acquired proinflammatory phenotype, and shared a similar lipid and metabolic profiling to human fatty livers. Biofabrication of genetically edited human liver tissue may become an important tool for investigating human liver biology and disease.

Reactive Oxygen Species in the Tumor Microenvironment: An Overview.

Reactive oxygen species (ROS) are important signaling molecules in cancer. The level of ROS will determine physiological effects. While high levels of ROS can cause damage to tissues and cell death, low levels of ROS can have a proliferative effect. ROS are produced by tumor cells but also cellular components that make up the tumor microenvironment (TME). In this review, we discuss the mechanisms by which ROS can affect the TME with particular emphasis on tumor-infiltrating leukocytes. Greater insight into ROS biology in this setting may allow for therapeutic manipulation of ROS levels in order to remodel the tumor microenvironment and increase anti-tumor activity.

Combination pembrolizumab plus chemotherapy: a new standard of care for patients with advanced non-small-cell lung cancer.

Until recently, the treatment of patients with advanced non-small-cell lung cancer (NSCLC) whose tumors did not have a targetable genetic alteration was cytotoxic chemotherapy alone. This treatment provided only modest survival benefit. The introduction of immune checkpoint inhibitors targeting programmed cell death 1 protein (PD-1) signaling pathway in the treatment of patients with NSCLC has had significant effect on patient survival. Atezolizumab, nivolumab and pembrolizumab have been shown to be superior to chemotherapy in patients with recurrent NSCLC. Recently, pembrolizumab has been combined with chemotherapy in the front-line setting and has demonstrated an improvement in overall survival in NSCLC patients as compared to chemotherapy alone. In this review we will focus on the clinical trials that led to approval of combination pembrolizumab and chemotherapy as first-line treatment for patients with advanced NSCLC as well as discuss other combinations of immunotherapy and chemotherapy that have also been evaluated.

Natural allelic variations in glutathione peroxidase-1 affect its subcellular localization and function.

Glutathione peroxidase 1 (GPx-1) has been implicated in the etiology of several common diseases due to the association between specific allelic variations and cancer risk. The most common among these variations are the codon 198 polymorphism that results in either a leucine or proline and the number of alanine repeat codons in the coding sequence. The molecular and biologic consequences of these variations remain to be characterized. Toward achieving this goal, we have examined the cellular location of GPx-1 encoded by allelic variants by ectopically expressing these genes in MCF-7 human breast carcinoma cells that produce undetectable levels of GPx-1, thus achieving exclusive expression in the same cellular environment. A differential distribution between the cytoplasm and mitochondria was observed, with the allele expressing the leucine-198 polymorphism and 7 alanine repeats being more cytoplasmically located than the other alleles examined. To assess whether the distribution of GPx-1 between the cytoplasm and mitochondria had a biologic consequence, we engineered derivative GPx-1 proteins that were targeted to the mitochondria by the addition of a mitochondria targeting sequence and expressed these proteins in MCF-7 cells. These cells were examined for their response to oxidative stress, energy metabolism, and impact on cancer-associated signaling molecules. The results obtained indicated that both primary GPx-1 sequence and cellular location have a profound impact on cellular biology and offer feasible hypotheses about how expression of distinct GPx-1 alleles can affect cancer risk. Cancer Res; 74(18); 5118-26. ©2014 AACR.

Algebraic and combinatorial properties of common RNA pseudoknot classes with applications.

Predicting RNA structures with pseudoknots in general is an NP-complete problem. Accordingly, several authors have suggested subclasses that provide polynomial time prediction algorithms by allowing (respectively, disallowing) certain structural motives. In this article, we introduce a unifying algebraic view on most of these classes. That way it becomes possible to find linear time recognition algorithms that decide whether or not a given structure is member of a class (we offer these algorithms as a web service to the scientific community). Furthermore, by presenting a general translation scheme of our algebraic descriptions into multiple context-free grammars, and proving a new correspondence of multiple context-free grammars and generating functions, it becomes possible to derive the precise asymptotic size of all the classes, solving some open problems such as enumerating the Rivas & Eddy class of pseudoknots.

Random generation of RNA secondary structures according to native distributions.

BACKGROUND: Random biological sequences are a topic of great interest in genome analysis since, according to a powerful paradigm, they represent the background noise from which the actual biological information must differentiate. Accordingly, the generation of random sequences has been investigated for a long time. Similarly, random object of a more complicated structure like RNA molecules or proteins are of interest. RESULTS: In this article, we present a new general framework for deriving algorithms for the non-uniform random generation of combinatorial objects according to the encoding and probability distribution implied by a stochastic context-free grammar. Briefly, the framework extends on the well-known recursive method for (uniform) random generation and uses the popular framework of admissible specifications of combinatorial classes, introducing weighted combinatorial classes to allow for the non-uniform generation by means of unranking. This framework is used to derive an algorithm for the generation of RNA secondary structures of a given fixed size. We address the random generation of these structures according to a realistic distribution obtained from real-life data by using a very detailed context-free grammar (that models the class of RNA secondary structures by distinguishing between all known motifs in RNA structure). Compared to well-known sampling approaches used in several structure prediction tools (such as SFold) ours has two major advantages: Firstly, after a preprocessing step in time O(n2) for the computation of all weighted class sizes needed, with our approach a set of m random secondary structures of a given structure size n can be computed in worst-case time complexity Om⋅n⋅ log(n) while other algorithms typically have a runtime in O(m⋅n2). Secondly, our approach works with integer arithmetic only which is faster and saves us from all the discomforting details of using floating point arithmetic with logarithmized probabilities. CONCLUSION: A number of experimental results shows that our random generation method produces realistic output, at least with respect to the appearance of the different structural motifs. The algorithm is available as a webservice at http://wwwagak.cs.uni-kl.de/NonUniRandGen and can be used for generating random secondary structures of any specified RNA type. A link to download an implementation of our method (in Wolfram Mathematica) can be found there, too.

Mitochondrial metabolism and ROS generation are essential for Kras-mediated tumorigenicity.

Otto Warburg's theory on the origins of cancer postulates that tumor cells have defects in mitochondrial oxidative phosphorylation and therefore rely on high levels of aerobic glycolysis as the major source of ATP to fuel cellular proliferation (the Warburg effect). This is in contrast to normal cells, which primarily utilize oxidative phosphorylation for growth and survival. Here we report that the major function of glucose metabolism for Kras-induced anchorage-independent growth, a hallmark of transformed cells, is to support the pentose phosphate pathway. The major function of glycolytic ATP is to support growth under hypoxic conditions. Glutamine conversion into the tricarboxylic acid cycle intermediate alpha-ketoglutarate through glutaminase and alanine aminotransferase is essential for Kras-induced anchorage-independent growth. Mitochondrial metabolism allows for the generation of reactive oxygen species (ROS) which are required for Kras-induced anchorage-independent growth through regulation of the ERK MAPK signaling pathway. We show that the major source of ROS generation required for anchorage-independent growth is the Q(o) site of mitochondrial complex III. Furthermore, disruption of mitochondrial function by loss of the mitochondrial transcription factor A (TFAM) gene reduced tumorigenesis in an oncogenic Kras-driven mouse model of lung cancer. These results demonstrate that mitochondrial metabolism and mitochondrial ROS generation are essential for Kras-induced cell proliferation and tumorigenesis.

Mitochondrial metabolism and cancer.

Historically, it has been assumed that glycolytic metabolism, not mitochondrial metabolism, is essential for tumor cell proliferation. However, most tumor cells have functional mitochondria, and recent studies suggest that the citric acid cycle (TCA) cycle intermediates are precursors for synthesis of nucleotides, lipids, and amino acids. Here we review the accumulating evidence that mitochondrial metabolism plays an essential role in tumor cell proliferation.

Reactive oxygen species-dependent signaling regulates cancer.

Historically, it has been assumed that oxidative stress contributes to tumor initiation and progression solely by inducing genomic instability. Recent studies indicate that reactive oxygen species are upregulated in tumors and can lead to aberrant induction of signaling networks that cause tumorigenesis and metastasis. Here we review the role of redox-dependent signaling pathways and transcription factors that regulate tumorigenesis.